Banafa A Quantum Computing and Other Transformative Technologies 2023
Banafa A Quantum Computing and Other Transformative Technologies 2023
Banafa A Quantum Computing and Other Transformative Technologies 2023
Series Editors
The “River Publishers Series in Computing and Information Science and Technology” covers research
which ushers the 21st Century into an Internet and multimedia era. Networking suggests transportation
of such multimedia contents among nodes in communication and/or computer networks, to facilitate the
ultimate Internet.
Theory, technologies, protocols and standards, applications/services, practice and implementa-
tion of wired/wireless
The “River Publishers Series in Computing and Information Science and Technology” covers
research which ushers the 21st Century into an Internet and multimedia era. Networking suggests
transportation of such multimedia contents among nodes in communication and/or computer networks,
to facilitate the ultimate Internet.
Theory, technologies, protocols and standards, applications/services, practice and implemen-
tation of wired/wireless networking are all within the scope of this series. Based on network and
communication science, we further extend the scope for 21st Century life through the knowledge
in machine learning, embedded systems, cognitive science, pattern recognition, quantum/biological/
molecular computation and information processing, user behaviors and interface, and applications
across healthcare and society.
Books published in the series include research monographs, edited volumes, handbooks and text-
books. The books provide professionals, researchers, educators, and advanced students in the field
with an invaluable insight into the latest research and developments.
Ahmed Banafa
Professor of Engineering at San Jose State University (USA)
and
Instructor of Continuing Studies at Stanford University (USA)
River Publishers
Published 2023 by River Publishers
River Publishers
Alsbjergvej 10, 9260 Gistrup, Denmark
www.riverpublishers.com
Preface xvii
Audience xix
Acknowledgment xxi
Introduction 1
2 Quantum Cryptography 9
2.1 Problems with using Quantum Cryptography . . . . . . . . . 10
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3 Quantum Internet 13
3.1 What is Quantum Internet? . . . . . . . . . . . . . . . . . . 14
3.2 Quantum Communications . . . . . . . . . . . . . . . . . . 15
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4 Quantum Teleportation 17
4.1 Quantum Teleportation: Paving the Way for a
Quantum Internet . . . . . . . . . . . . . . . . . . . . . . . 19
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
vii
viii Contents
10 Affective Computing 49
10.1 Emotion in Machines . . . . . . . . . . . . . . . . . . . . . 50
10.2 The Future . . . . . . . . . . . . . . . . . . . . . . . . . . 51
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
11 Autonomic Computing 53
11.1 Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
11.2 Future of Autonomic Computing. . . . . . . . . . . . . . . 55
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Part 3 Big Data, Dark Data, Thick Data, and Small Data 57
12 Thick Data vs. Big Data 59
12.1 Comparison of Big Data and Thick Data . . . . . . . . . . 60
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
36 Your Smart Device Will Feel Your Pain and Fear 189
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
References 217
Index 227
xvii
Audience
This is book is for everyone who would like to have a good understanding of
Quantum Computing and its applications and its relationship with business
operations, and also gain insight to other transformative technologies like
IoT, Cloud Computing, Deep Learning, Blockchain, Big Data and Wearable
Technologies. Audience includes:
C-Suite executives, IT managers, marketing & sales professionals,
lawyers, product & project managers, business professionals, journalists,
students.
xix
Acknowledgment
I am grateful for all the support I received from my family during the stages
of writing this book.
xxi
List of Figures
xxiii
List of Abbreviations
xxv
xxvi List of Abbreviations
IP Internet protocol
IPS Intrusion prevention system
LPA Least privilege access
MaaS Metaverse as a service
ML Machine learning
MLP Machine learning poisoning
NAT Network address translation
NFV Network functions virtualization
NFV Network functions virtualization
NISQ Noisy intermediate scale quantum
NSA National security agency
PaaS Platforms-as-a-service
PAN Personal area network
PCI Payment card industry
QAI Quantum artificial intelligence
QCaaS Quantum computing as a service
QIaaS Quantum infrastructure as a service
QIoT Quantum IoT
QoS Quality of service
QPaaS Quantum platform as a service
QSaaS Quantum software as a service
RFID Radio-frequency identification
ROI Return on investment
RSA Rivest, Shamir, Adelman
SAN Storage area network
SCM Supply chain management
SDN Software-defined networking
SEO Search engine optimization
SNCA Sensors, networks, cloud, and applications
SOX Sarbanes-oxley act
SSL Secure sockets layer
SSP Safety, security, and privacy
TCO Total cost of ownership
TCP Transmission control protocol
UQC Universal quantum computer
VC Venture capital
VR Virtual reality
List of Abbreviations xxvii
1
PART 1
Quantum Computing
1
What is Quantum Computing?
5
6 What is Quantum Computing?
References
[1] http://www.fastcolabs.com/3013214/why-quantum-computing-is-
faster-for-everything-but-the-web
[2] http://www.theguardian.com/science/2014/mar/06/quantum-
computing-explained-particle-mechanics
[3] http://www.economist.com/news/science-and-technology/21578027-
first-real-world-contests-between-quantum-computers-and-standard-
ones-faster
[4] http://whatis.techtarget.com/definition/quantum-computing
[5] http://physics.about.com/od/quantumphysics/f/quantumcomp.htm
2
Quantum Cryptography
9
10 Quantum Cryptography
assigned to each photon – for example, a photon that has a vertical spin ( | )
can be assigned a 1.
“If you build it correctly, no hacker can hack the system. The question
is what it means to build it correctly,” said physicist Renato Renner from the
Institute of Theoretical Physics in Zurich [9].
Regular, non-quantum encryption can work in a variety of ways, but,
generally, a message is scrambled and can only be unscrambled using a secret
key. The trick is to make sure that whomever you are trying to hide your com-
munication from does not get their hands on your secret key. Cracking the
private key in a modern cryptosystem would generally require figuring out
the factors of a number that is the product of two insanely huge prime num-
bers. The numbers are chosen to be so large that, with the given processing
power of computers, it would take longer than the lifetime of the universe for
an algorithm to factor their product.
But such encryption techniques have their vulnerabilities. Certain prod-
ucts – called weak keys – happen to be easier to factor than others. Also,
Moore’s law continually ups the processing power of our computers. Even
more importantly, mathematicians are constantly developing new algorithms
that allow for easier factorization.
Quantum cryptography avoids all these issues. Here, the key is encrypted
into a series of photons that get passed between two parties trying to share
secret information. The Heisenberg uncertainty principle dictates that an
adversary cannot look at these photons without changing or destroying them.
“In this case, it doesn’t matter what technology the adversary has,
they’ll never be able to break the laws of physics,” said physicist Richard
Hughes of Los Alamos National Laboratory in New Mexico, who works on
quantum cryptography [10].
References
[6] http://www.qi.damtp.cam.ac.uk/node/38
[7] http://www.businessinsider.com/what-is-quantum-encryption-2014-
3#ixzz33jYuMw48
[8] http://www.wired.com/2013/06/quantum-cryptography-hack/
[9] http://searchsecurity.techtarget.com/definition/quantum-cryptography
[10] http://science.howstuffworks.com/science-vs-myth/everyday-myths/
quantum-cryptology.htm
[11] http://www.wisegeek.com/what-is-quantum-cryptography.htm
[12] http://www.techrepublic.com/blog/it-security/how-quantum-
cryptography-works-and-by-the-way-its-breakable/
3
Quantum Internet
13
14 Quantum Internet
based on the idea that quantum internet exists in parallel to the current eco-
system of companies we have in regular internet.
The “traditional internet,” as the regular internet is sometimes called,
will still exist. It is expected that large organizations will rely on the quantum
internet to safeguard data, but those individual consumers will continue to
use the classical internet [13].
Experts predict that the financial sector will benefit from the quantum
internet when it comes to securing online transactions. The healthcare sec-
tors and the public sectors are also expected to see benefits. In addition to
providing a faster, safer internet experience, quantum computing will better
position organizations to solve complex problems, like supply chain manage-
ment. Furthermore, it will expedite the exchange of vast amounts of data, and
carrying out large-scale sensing experiments in astronomy, materials discov-
ery and life sciences [13, 15].
But first let us explain some of the basic terms of the quantum world:
Quantum computing is the area of study focused on developing computer
technology based on the principles of quantum theory. The quantum com-
puter, following the laws of quantum physics, would gain enormous process-
ing power through the ability to be in multiple states and to perform tasks
using all possible permutations simultaneously [14].
In a quantum computer, a number of elemental particles such as elec-
trons or photons can be used with either their charge or polarization acting
as a representation of 0 and/or 1. Each of these particles is known as a quan-
tum bit, or qubit; the nature and behavior of these particles form the basis of
quantum computing [14].
means leveraging the behavior of particles when taken at their smallest scale –
so-called “quantum states.”
Unsurprisingly, qubits cannot be used to send the kind of data we are
familiar with, like emails and WhatsApp messages. But the strange behavior of
qubits is opening up huge opportunities in other, more niche applications [13].
References
[13] https://www.cybertalk.org/2020/10/23/quantum-internet-fast-forward-
into-the-future/
[14] https://www.bbvaopenmind.com/en/technology/digital-world/quantum-
computing/
[15] https://www.zdnet.com/article/what-is-the-quantum-internet-
everything-you-need-to-know-about-the-weird-future-of-quantum-
networks/
[16] https://ahmedbanafa.blogspot.com/2014/06/understanding-quantum-
cryptography.html
4
Quantum Teleportation
17
18 Quantum Teleportation
References
[17] https://en.wikipedia.org/wiki/Quantum_teleportation
[18] https://www.linkedin.com/pulse/quantum-internet-explained-ahmed-
banafa/
[19] https://www.designboom.com/technology/nasa-long-distance-
quantum-teleportation-12-22-2020/
[20] https://www.siliconrepublic.com/machines/quantum-computing-
fermilab
5
Quantum Computing and IoT
21
22 Quantum Computing and IoT
References
[21] https://ahmedbanafa.blogspot.com/2019/12/ten-trends-of-iot-in-2020.
html
[22] https://ahmedbanafa.blogspot.com/2020/11/quantum-internet-
explained.html
[23] https://www.azoquantum.com/Article.aspx?ArticleID=101
[24] https://www.cybersecurityintelligence.com/blog/quantum-computing-
the-internet-of-things-and-hackers-4914.html
[25] https://www.europeanbusinessreview.com/iot-security-are-we-
ready-for-a-quantum-world/
[26] https://www.bbvaopenmind.com/en/technology/digital-world/quantum-
computing-and-blockchain-facts-and-myths/
[27] https://www.ft.com/content/c13dbb51-907b-4db7-8347-30921ef
6
Quantum Computing and Blockchain:
Myths and Facts
27
28 Quantum Computing and Blockchain
key. The trick is to make sure that whomever you are trying to hide your
communication from does not get their hands on your secret key. Cracking
the private key in a modern cryptosystem would generally require figuring
out the factors of a number that is the product of two insanely huge prime
numbers.
The numbers are chosen to be so large that, with the given processing
power of computers, it would take longer than the lifetime of the universe for
an algorithm to factor their product.
Encryption techniques have their vulnerabilities. Certain products –
called weak keys – happen to be easier to factor than others. Also, Moore’s
law continually ups the processing power of our computers. Even more
importantly, mathematicians are constantly developing new algorithms that
allow for easier factorization.
Quantum cryptography avoids all these issues. Here, the key is encrypted
into a series of photons that get passed between two parties trying to share
secret information. The Heisenberg uncertainty principle dictates that an
adversary cannot look at these photons without changing or destroying them.
“In this case, it doesn’t matter what technology the adversary has,
they’ll never be able to break the laws of physics,” said physicist Richard
Hughes of Los Alamos National Laboratory in New Mexico, who works on
quantum cryptography [32, 33].
References
[28] https://www.forbes.com/sites/billybambrough/2019/10/02/could-google-
be-about-to-break-bitcoin/#1d78c5373329
[29] https://decrypt.co/9642/what-google-quantum-computer-means-for-
bitcoin/
[30] https://www.coindesk.com/how-should-crypto-prepare-for-googles-
quantum-supremacy?
[31] https://www.ccn.com/google-quantum-bitcoin/
[32] https://www.linkedin.com/pulse/20140503185010-246665791-
quantum-computing/
[33] https://www.linkedin.com/pulse/20140608053056-246665791-under-
standing-quantum-
7
Quantum Computing and AI:
A Mega-Buzzword
31
32 Quantum Computing and AI
optimizes the same for solving all kinds of business problems to make better
decisions [35].
research cycle from test; tracing and treating of the virus can decrease finan-
cial implosion in the banking sector and improve the logistics chain in the
manufacturing industry [35].
References
[34] https://www.linkedin.com/pulse/quantum-computing-blockchain-facts-
myths-ahmed-banafa/
[35] https://analyticsindiamag.com/will-quantum-computing-define-the-
future-of-ai/
References 35
[36] https://www.analyticsinsight.net/ai-quantum-computing-can-enable-
much-anticipated-advancements/
[37] https://research.aimultiple.com/quantum-ai/
[38] https://www.globenewswire.com/news-release/2020/11/17/2128495/0/
en/Quantum-Computing-Market-is-Expected-to-Reach-2-2-Billion-
by-2026.html
[39] https://ai.googleblog.com/2019/10/quantum-supremacy-using-
programmable.html
8
Quantum Computing Trends
37
38 Quantum Computing Trends
is, they will remain entangled as long as they are isolated. Taken together,
quantum superposition and entanglement create an enormously enhanced
computing power [42].
Quantum computers fall into four categories [40]:
1. Quantum emulator/simulator
2. Quantum annealer
3. Noisy intermediate scale quantum (NISQ)
4. Universal quantum computer – which can be a cryptographically rele-
vant quantum computer (CRQC)
References
[40] https://www.linkedin.com/pulse/quantum-technology-ecosystem-
explained-steve-blank/?
42 Quantum Computing Trends
[41] https://www.bbvaopenmind.com/en/technology/digital-world/
quantum-computing-and-ai/
[42] https://phys.org/news/2022-03-technique-quantum-resilient-noise-
boosts.html
[43] https://thequantuminsider.com/2019/10/01/introduction-to-
qubits-part-1/
PART 2
Other Computing Technologies
9
What is Deep Learning?
45
46 What is Deep Learning?
amounts of data and rules about data relationships (for example, “A grand-
father is older than a person’s father”). A program can then tell the network
how to behave in response to an external stimulus (for example, to input from
a computer user who is interacting with the network) or can initiate activity
on its own (within the limits of its access to the external world) [44, 45].
Last year, Facebook established the AI Research Unit, using deep learn-
ing expertise to help create solutions that will better identify faces and objects
in the 350 million photos and videos uploaded to Facebook each day.
An example of deep learning in action is voice recognition like Google
Now and Apple’s Siri.
References
[44] http://www.technologyreview.com/news/524026/is-google-cornering-the-
market-on-deep-learning/
[45] http://www.forbes.com/sites/netapp/2013/08/19/what-is-deep-learning/
[46] http://www.fastcolabs.com/3026423/why-google-is-investing-in-deep-
learning
[47] http://www.npr.org/blogs/alltechconsidered/2014/02/20/280232074/deep-
learning-teaching-computers-to-tell-things-apart
[48] http://www.technologyreview.com/news/519411/facebook-launches-
advanced-ai-effort-to-find-meaning-in-your-posts/
[49] http://www.deeplearning.net/tutorial/
[50] http://searchnetworking.techtarget.com/definition/neural-network
10
Affective Computing
49
50 Affective Computing
The more computers we have in our lives, the more we are going to
want them to behave politely, and be socially smart. We do not want it to
bother us with unimportant information. That kind of common-sense reason-
ing requires an understanding of the person’s emotional state [51].
One way to look at affective computing is human–computer interaction
in which a device has the ability to detect and appropriately respond to its
user’s emotions and other stimuli. A computing device with this capacity
could gather cues to user emotion from a variety of sources. Facial expres-
sions, posture, gestures, speech, the force or rhythm of key strokes, and the
temperature changes of the hand on a mouse can all signify changes in the
user’s emotional state, and these can all be detected and interpreted by a
computer. A built-in camera captures images of the user and algorithms are
used to process the data to yield meaningful information. Speech recognition
and gesture recognition are among the other technologies being explored for
affective computing applications [52].
Recognizing emotional information requires the extraction of meaning-
ful patterns from the gathered data. This is done using machine learning tech-
niques that process different modalities, such as speech recognition, natural
language processing, or facial expression detection.
References
[51] https://en.wikipedia.org/wiki/Affective_computing
[52] http://www.gartner.com/it-glossary/affective-computing
[53] http://whatis.techtarget.com/definition/affective-computing
[54] http://curiosity.discovery.com/question/what-is-affective-computing
11
Autonomic Computing
53
54 Autonomic Computing
11.1 Benefits
The main benefit of autonomic computing is reduced total cost of owner-
ship (TCO). Breakdowns will be less frequent, thereby drastically reducing
maintenance costs. Fewer personnel will be required to manage the sys-
tems. “The most immediate benefit of autonomic computing will be reduced
deployment and maintenance cost , time and increased stability of IT sys-
tems through automation,” says Dr. Kumar of IBM. “Higher order benefits
will include allowing companies to better manage their business through IT
systems that are able to adopt and implement directives based on business
policy, and are able to make modifications based on changing environments.”
Another benefit of this technology is that it provides server consolidation to
maximize system availability and minimizes cost and human effort to man-
age large server farms [58].
References
[55] http://computer.financialexpress.com/20020819/focus1.shtml
[56] http://www.webopedia.com/TERM/A/autonomic_computing.html
[57] http://www.techopedia.com/definition/191/autonomic-computing
[58] http://whatis.techtarget.com/definition/autonomic-computing
PART 3
Big Data, Dark Data, Thick Data, and
Small Data
12
Thick Data vs. Big Data
59
60 Thick Data vs. Big Data
who do not understand why, how, and when their customers decide to make
purchases for example [60].
To tackle this pain point, companies might need to consider an alterna-
tive to big data, namely thick data; it is helpful to define both terms, big data
vs. thick data [61].
Big data is large and complex unstructured data, defined by 3 Vs.
Volume: with big data, you will have to process high volumes of low-density,
unstructured data. This can be data of unknown value, such as Facebook
actions, Twitter data feeds, clickstreams on a web page or a mobile app, or
sensor-enabled equipment. For some organizations, this might be tens of
terabytes of data. For others, it may be hundreds of petabytes. Velocity: it
is the fast rate at which data is received and acted on. Variety: it refers to
the many types of data that are available. Unstructured and semi-structured
data types, such as text, audio, and video, require additional preprocessing to
derive meaning and support metadata.
Thick data is about a complex range of primary and secondary research
approaches, including surveys, questionnaires, focus groups, interviews, jour-
nals, videos, and so on. It is the result of the collaboration between data sci-
entists and anthropologists working together to make sense of large amounts
of data. Together, they analyze data, looking for qualitative information like
insights, preferences, motivations, and reasons for behaviors. At its core,
thick data is qualitative data (like observations, feelings, and reactions) that
provides insights into consumers’ everyday emotional lives. Because thick
data aims to uncover people’s emotions, stories, and models of the world they
live in, it can be difficult to quantify.
Facebook say they want to do. To “understand the world,” you need to c apture
both its (big data) quantities and its (thick data) qualities.
In fact, companies that rely too much on the numbers, graphs, and fac-
toids of big data risk insulating themselves from the rich, qualitative reality
of their customers’ everyday lives. They can lose the ability to imagine and
intuit how the world – and their own businesses – might be evolving. By out-
sourcing our thinking to big data, our ability to make sense of the world by
careful observation begins to wither, just as you miss the feel and texture of a
new city by navigating it only with the help of a GPS [64, 68, 69].
Successful companies and executives work to understand the emotional,
even visceral context in which people encounter their product or service, and
they are able to adapt when circumstances change. They are able to use what
we like to call thick data which comprises the human element of big data.
One promising technology that can give us the best of both worlds (big
data and thick data) is affective computing.
Affective computing is the study and development of systems and
devices that can recognize, interpret, process, and simulate human affects. It
is an interdisciplinary field spanning computer science, psychology, and cog-
nitive science. While the origins of the field may be traced as far back as to
early philosophical enquiries into emotion (“affect” is, basically, a synonym
for “emotion”), the more modern branch of computer science originated with
Rosalind Picard’s 1995 paper on affective computing. A motivation for the
research is the ability to simulate empathy. The machine should interpret the
emotional state of humans and adapt its behavior to them, giving an appro-
priate response for those emotions [65, 66, 67].
Using affective computing algorithms in gathering and processing data
will make the data more human and show both sides of data: quantitative and
qualitative.
References
[59] https://www.linkedin.com/pulse/8-key-tech-trends-post-covid-19-world-
ahmed-banafa/
[60] https://www.bdex.com/thick-data-why-marketers-must-understand-why-
people-behave-the-way-they-do/
[61] https://www.usertesting.com/blog/thick-data-vs-big-data
[62] https://www.oracle.com/in/big-data/what-is-big-data/
[63] https://www.cognizant.com/us/en/glossary/thick-data
[64] http://www.brandwatch.com/2014/04/what-is-thick-data-and-why-
should-you-use-it/
References 63
[65] http://ethnographymatters.net/2013/05/13/big-data-needs-thick-data/
[66] http://www.wired.com/2014/04/your-big-data-is-worthless-if-you-
dont-bring-it-into-the-real-world/
[67] h t t p : / / w w w. b i g - d a t a f o r u m . c o m / 2 3 8 / b i g - d a t a - h ow - a b o u t -
%E2%80%9Cthick-data%E2%80%9D-%E2%80%94-or-did-we-just-
create-another-haystack
[68] http://blog.marketresearch.com/thick-data-and-market-research-
understanding-your-customers
[69] http://www.wired.com/2013/03/clive-thompson-2104/
13
Understanding Dark Data
Gartner defines dark data as the information assets that organizations collect,
process, and store during regular business activities, but generally fail to use
for other purposes (for example, analytics, business relationships, and direct
monetizing). Similar to dark matter in physics, dark data often comprises
most organizations’ universe of information assets. Thus, organizations
often retain dark data for compliance purposes only. Storing and securing
data typically incurs more expense (and sometimes greater risk) than value
[70, 71, 73].
Dark data is a type of unstructured, untagged, and untapped data that
is found in data repositories and has not been analyzed or processed. It is
similar to big data but differs in how it is mostly neglected by business and IT
administrators in terms of its value.
Dark data is also known as dusty data.
Dark data is data that is found in log files and data archives stored within
large enterprise class data storage locations. It includes all data objects and
types that have yet to be analyzed for any business or competitive intelli-
gence or aid in business decision making. Typically, dark data is complex to
65
66 Understanding Dark Data
analyze and store in locations where analysis is difficult. The overall process
can be costly. It also can include data objects that have not been seized by the
enterprise or data that are external to the organization, such as data stored by
partners or customers.
IDC stated that up to 90% of big data is dark data.
With the growing accumulation of structured, unstructured, and
semi-structured data in organizations – increasingly through the adoption of
big data applications – dark data has come especially to denote operational
data that is left unanalyzed. Such data is seen as an economic opportunity for
companies if they can take advantage of it to drive new revenues or reduce
internal costs. Some examples of data that is often left dark include server
log files that can give clues to website visitor behavior, customer call detail
records that can indicate consumer sentiment, and mobile geo-location data
that can reveal traffic patterns to aid in business planning.
Dark data may also be used to describe data that can no longer be
accessed because it has been stored on devices that have become obsolete
[74, 75].
References
[70] http://h30458.www3.hp.com/us/us/discover-performance/info-
management-leaders/2014/jun/tapping-the-profit-potential-of-dark-
data.html
68 Understanding Dark Data
[71] http://h30458.www3.hp.com/ww/en/ent/You-have-dark-data_1392257.
html
[72] http://www.gartner.com/it-glossary/dark-data
[73] http://www.techopedia.com/definition/29373/dark-data
[74] http://searchdatamanagement.techtarget.com/definition/dark-data
[75] http://www.computerweekly.com/opinion/Dark-data-could-halt-
big-datas-path-to-success
[76] http://www.forbes.com/sites/gartnergroup/2014/05/07/digital-business-
is-everyones-business/
[77] https://medium.com/what-i-learned-building/7d88d014ba98
[78] http://blogs.pb.com/digital-insights/2014/05/05/dark-data-analytics/
[79] http://blogs.computerworld.com/business-intelligenceanalytics/23286/
dark-data-when-it-worth-being-brought-light
14
Small Data vs. Big Data: Back to the Basics
Small data is data in a volume and format that makes it accessible, informa-
tive, and actionable.
The small data group offers the following explanation:
Small data connects people with timely, meaningful insights
(derived from big data and/or “local” sources), organized and
packaged – often visually – to be accessible, understandable, and
actionable for everyday tasks.
This definition applies to the data we have, as well as the end-user apps and
analyst workbenches for turning big data sets into actionable small data. The
key “action” words here are connect, organize, and package, and the “value”
is rooted in making insights available to all (accessible), easy to apply (under-
standable), and focused on the task at hand (actionable) [80, 81].
The term small data contrasts with big data, which usually refers to
a combination of structured and unstructured data that may be measured in
petabytes or exabytes. Big data is often said to be characterized by three Vs:
the volume of data, the variety of types of data, and the velocity at which it
69
70 Small Data vs. Big Data
is processed, all of which combine to make big data very difficult to manage.
Small data, in contrast, consists of usable chunks.
The idea of big data is compelling: want to uncover hidden patterns
about customer behavior, predict the next election, or see where to focus ad
spend? There is an app for that. And to listen to the pundits, we should all be
telling our kids to become data scientists, since every company will need to
hire an army of them to survive the next wave of digital disruption.
Yet, all the steam coming out of the big data hype machine seems to be
obscuring our view of the big picture: in many cases, big data is overkill. And
in most cases, big data is useful only if we (those of us who are not data sci-
entists) can do something with it in our everyday jobs, which is where small
data enters the picture.
At its core, the idea of small data is that businesses can get actionable
results without acquiring the kinds of systems commonly used in big data
analytics.
A company might invest in a whole lot of server storage and use sophis-
ticated analytics machines and data mining applications to scour a network
for lots of different bits of data, including dates and times of user actions,
demographic information, and much more. All of this might get funneled into
a central data warehouse, where complex algorithms sort and process the data
to display it in detailed reports. While these kinds of processes have benefited
businesses in a lot of ways, many enterprises are finding that these measures
require a lot of effort, and that in some cases, similar results can be achieved
using much less robust data mining strategies.
Small data is one of the ways that businesses are now drawing back
from a kind of obsession with the latest and newest technologies that support
more sophisticated business processes. Those promoting small data contend
that it is important for businesses to use their resources efficiently and avoid
overspending on certain types of technologies [83, 84].
we check in, search, browse, post etc., creating a unique signature that
provides a glimpse into our digital and physical health.
• Small data is at the center of the new CRM: Social CRM is used to
create a complete picture of customers, their segments, influencers, and
even competitors; we need to combine insights from social channels
and campaigns with web analytics and transactional data. Small data is
the key to building these rich profiles that will be the center of the new
CRM solutions.
• ROI: A focus on the last mile of big data offers to leverage investments
in small data ($10 billion and counting according to IDC) spent on
upstream systems, tools, and services.
• Data-driven marketing is the next wave: Big (and small) data-driven
marketing has the potential to revolutionize the way businesses inter-
act with customers, transform how customers access and consume (and
even wear) useful data, and ultimately redefine the relationship between
buyers and sellers.
• Consumer examples abound: Consumers have seen the potential of
small data to streamline their shopping, power their fitness routine, or
deliver recommendations about the best price for their next flight. With
more smart, wearable data-driven devices on the way, there are prom-
ises to be even more market demand for packaged data and data-deliv-
ery devices that “fit” the needs of everyday consumers.
• Platform and tool vendors are starting to pay attention: The promise
of operationalizing big data and “turning insight into action” is a major
tone from many of the big names in tech.
• It is about the end-user: Small data is about the end-user, what they
need, and how they can take action. Focus on the user first, and a lot of
our technology decisions become clearer.
• Simple: Small data is the right data; some small data will start life as
big data, but you should not need to be a data scientist to understand or
apply it for everyday tasks.
iron,” but decentralized data wrangling. Not “one ring to rule them all” but
“small pieces loosely joined.”
The real revolution is the mass democratization of the means of access,
storage, and processing of data; it is not about large organizations running
parallel software on tens of thousands of servers, but about more people than
ever being able to collaborate effectively around a distributed ecosystem of
information, an ecosystem of small data.
For many problems and questions, small data in itself is enough. The
data on my household energy use, the times of local buses, and government
spending are all small data. Everything processed in Excel is small data. And
when we want to scale up the way to do that is through componentized small
data: by creating and integrating small data “packages” not building big data
monoliths, by partitioning problems in a way that works across people and
organizations, not through creating massive centralized silos.
This next decade belongs to distributed models not centralized ones, to
collaboration not control, and to small data not big data [85, 86, 87].
References
[80] http://www.theguardian.com/news/datablog/2013/apr/25/forget-big-
data-small-data-revolution
[81] http://whatis.techtarget.com/definition/small-data
[82] http://www.zdnet.com/10-reasons-2014-will-be-the-year-of-small-
data-7000023667/
[83] http://www.techopedia.com/definition/29539/small-data
[84] http://technologies.lesechos.fr/partners/capgemini/cacheDirectory/
HTMLcontributions/img/20120711152005_BigData.jpeg
[85] http://www.312analytics.com/wp-content/uploads/2013/03/big-data-
versus-small-data1.jpg
[86] http://www.b-eye-network.com/blogs/oneal/Big%20data%20
Small%20data%20v4.png
[87] https://www.rd-alliance.org/system/files/800px-BigData_SmallData.png
15
What is a Data Lake?
“Data lake” is a massive, easily accessible data repository for storing “big
data.” Unlike traditional data warehouses, which are optimized for data anal-
ysis by storing only some attributes and dropping data below the level aggre-
gation, a data lake is designed to retain all attributes, especially when you do
not yet know what the scope of data or its use is [88, 89, 90].
73
74 What is a Data Lake?
modes, and it should support all types of data along with new data
sources [94, 95].
2. Data storage: A highly scalable data storage system should be able to
store and process raw data and support encryption and compression
while remaining cost-effective.
3. Data security: Regardless of the type of data processed, data lakes
should be highly secure from the use of multi-factor authentication,
authorization, role-based access, data protection, etc.
4. Data analytics: After data is ingested, it should be quickly and effi-
ciently analyzed using data analytics and machine learning tools to
derive valuable insights and move vetted data into a data warehouse.
5. Data governance: The entire process of data ingestion, preparation, cat-
aloging, integration, and query acceleration should be streamlined to
produce enterprise-level data quality. It is also important to track the
changes to key data elements for a data audit.
Like big data, the term data lake is sometimes disparaged as being simply
a marketing label for a product that supports it. However, the term is being
accepted as a way to describe any large data pool in which the schema and
data requirements are not defined until the data is queried.
The data lake promises to speed up the delivery of information and
insights to the business community without the hassles imposed by IT-centric
data warehousing processes.
each of these companies, the data lake created a value chain through which
new types of business value emerged:
• Using data lakes for web data increased the speed and quality of web
search.
• Using data lakes for clickstream data supported more effective methods
of web advertising.
• Using data lakes for cross-channel analysis of customer interactions
and behaviors provided a more complete view of the customer.
• Data lakes can give retailers profitable insights from raw data, such as
log files, streaming audio and video, text files, and social media content,
among other sources, to quickly identify real-time consumer behavior
and convert actions into sales. Such 360º profile views allow stores to
better interact with customers and push on-the-spot, customized offers
to retain business or acquire new sales.
• Data lakes can help companies improve their R&D performance by
allowing researchers to make more informed decisions regarding the
wealth of highly complex data assets that feed advanced predictive and
prescriptive analytics.
• Companies can use data lakes to centralize disparate data generated
from a variety of sources and run analytics and ML algorithms to be the
first to identify business opportunities. For instance, a biotechnology
company can implement a data lake that receives manufacturing data,
research data, customer support data, and public data sets and provide
real-time visibility into the research process for various user communi-
ties via different user interfaces.
Regardless of where you are now, take some time to look to the future. We
are on a journey toward connecting enterprise data together. As business is
increasingly becoming pure digital, access to data will become a critical pri-
ority, as will speed of development and deployment. The data lake is a dream
that can match those demands. The global data lake market was valued at
$7.9 billion in 2019 and is expected to grow at a compound annual growth
rate (CAGR) of 20.6% by 2024 to reach $20.1 billion [102, 103].
References
[88] https://www.bmc.com/blogs/data-lake-vs-data-warehouse-vs-database-
whats-the-difference/
[89] https://www.guru99.com/data-lake-architecture.html#21
78 What is a Data Lake?
[90] https://www.dataversity.net/data-lakes-what-they-are-and-how-to-
use-them/
[91] http://www.gartner.com/newsroom/id/2809117?
[92] http://datascience101.wordpress.com/2014/03/12/what-is-a-data-lake/
[93] http://en.wiktionary.org/wiki/data_lake
[94] http://searchaws.techtarget.com/definition/data-lake
[95] http://www.forbes.com/sites/edddumbill/2014/01/14/the-data-
lake-dream/
[96] http://www.platfora.com/wp-content/uploads/2014/06/data-lake.png
[97] http://www.b-eye-network.com/blogs/eckerson/archives/2014/03/
beware_of_the_a.php
[98] http://usblogs.pwc.com/emerging-technology/the-future-of-
big-data-data-lakes/
[99] http://siliconangle.com/blog/2014/08/07/gartner-drowns-the-
concept-of-data-lakes-in-new-report/
[100] http://www.pwc.com/us/en/technology-forecast/2014/issue1/features/
data-lakes.jhtml
[101] http://www.ibmbigdatahub.com/blog/don%E2%80%99t-drown-big-
data-lake http://www.wallstreetandtech.com/data-management/what-
is-a-data-lake/d/d-id/1268851?
[102] http://emcplus.typepad.com/.a/6a0168e71ada4c970c01a3fc-
c11630970b-800wi
[103] h t t p : / / h o r t o n w o r k s . c o m / w p - c o n t e n t / u p l o a d s / 2 0 1 4 / 0 5 /
TeradataHortonworks_Datalake_White-Paper_20140410.pdf
PART 4
Cloud Computing
16
Edge Computing Paradigm
81
82 Edge Computing Paradigm
data that needs to live on the edge. From there, administrators are able
to tie-in analytics, security, or other services directly into their cloud
model.
the day of the big parade. A surge of traffic into the city is expected as revel-
ers come to celebrate their team’s win. As the traffic builds, data are collected
from individual traffic lights. The application developed by the city to adjust
light patterns and timing is running on each edge device. The app automat-
ically makes adjustments to light patterns in real time, at the edge, working
around traffic impediments as they arise and diminish. Traffic delays are kept
to a minimum, and fans spend less time in their cars and have more time to
enjoy their big day [106].
After the parade is over, all the data collected from the traffic light
system would be sent up to the cloud and analyzed, supporting predictive
analysis and allowing the city to adjust and improve its traffic application’s
response to future traffic anomalies. There is little value in sending a live
steady stream of everyday traffic sensor data to the cloud for storage and
analysis. The civic engineers have a good handle on normal traffic patterns.
The relevant data is sensor information that diverges from the norm, such as
the data from parade day.
and failover solutions that safeguard those processes will become even more
essential. Generally speaking, we are moving toward localization to distrib-
uted model away from the current strained centralized system defining the
internet infrastructure [107, 108].
References
[104] https://www.linkedin.com/pulse/why-iot-needs-fog-computing-
ahmed-banafa/
[105] https://www.linkedin.com/pulse/fog-computing-vital-successful-
internet-things-iot-ahmed-banafa/
[106] http://www.cisco.com/web/about/ac50/ac207/crc_new/university/
RFP/rfp13078.html
[107] http://www.howtogeek.com/185876/what-is-Edge-computing/
[108] http://newsroom.cisco.com/feature-content?type=webcontent&
articleId=1365576
17
The Internet of Everything
The Internet of Everything was listed as one of the top tech trends. The term
Internet of Everything (IoE) is a fairly new term, and there is a confusion
about the difference between the Internet of Everything (IoE) and the Internet
of Things (IoT); to clarify that, let us start with definitions and applications
and explore the future of this new concept [109, 110].
87
88 The Internet of Everything
References
[109] http://www.cisco.com/web/about/ac79/innov/IoE.html
[110] http://internetofeverything.cisco.com/
[111] http://www.cisco.com/web/solutions/trends/iot/overview.html
[112] http://time.com/#539/the-next-big-thing-for-tech-the-internet-of-
everything/
[113] http://www.gartner.com/newsroom/id/2621015
90 The Internet of Everything
[114] http://www.livemint.com/Specials/34DC3bDLSCItBaTfRvMBQO/
Internet-of-Everything-gains-momentum.html
[115] http://www.tibco.com/blog/2013/10/07/gartners-internet-of-everything/
[116] http://www.eweek.com/small-business/internet-of-everything-personal-
worlds-creating-new-markets-gartner.html
[117] “Secure and Smart IoT” Book, Ahmed Banafa
[118] https://www.linkedin.com/pulse/20140319132744-246665791-the-
internet-of-everything-ioe/
18
Content Delivery Networks – CDNs
91
92 Content Delivery Networks – CDNs
fact that it inherently offers enhanced data backup, archiving, and storage
capacity. This can benefit individuals and enterprises that rely on online data
backup.
A complete CDN architecture is made up of various individual compo-
nents working toward the common goal of delivering service to the end-user
community. A common example of a CDN can be a consolidated file server
that is used as the user application and data file warehouse. The common
functions associated with the content delivery network include file accessi-
bility, application processing, multimedia delivery, and caching. A complete
CDN has the ability to exhibit functionalities that are only possible because
of the participation of each separate CDN component.
The strategically placed servers have a higher capacity compared to a
network backbone, which maximizes the potential to increase the number of
simultaneous users. In addition, such strategically placed edge servers lower
the delivery time and decrease load on public and private peers, backbones,
and interconnects. A CDN manages the full load of traffic by readdressing it
toward the edge servers [123].
References
[119] http://www.webopedia.com/TERM/C/CDN.html
96 Content Delivery Networks – CDNs
[120] http://searchaws.techtarget.com/definition/content-delivery-
network-CDN
[121] http://en.wikipedia.org/wiki/Content_delivery_network
[122] http://www.akamai.com/html/solutions/sola_cdn.html
[123] http://www.techopedia.com/definition/4191/content-delivery-
network-cdn
[124] http://www.pcmag.com/encyclopedia/term/39466/cdn
19
Network Functions Virtualization (NFV) or
Software-Defined Networking (SDN)?
97
98 Network FunctionsVirtualization (NFV) or Software-Defined Networking (SDN)?
network to keep pace with the innovations of all the people and devices it is
connecting [129].
References
[125] http://www.6wind.com/software-defined-networking/sdn-nfv-primer/
[126] http://www.tmcnet.com/tmc/whitepapers/documents/whitepapers/
2013/9377-network-functions-virtualization-challenges-solutions.pdf
[127] http://www.sdncentral.com/why-sdn-software-defined-networking-
or-nfv-network-functions-virtualization-now/
[128] http://www.sdncentral.com/technology/nfv-and-sdn-whats-the-
difference/2013/03/
[129] http://www.sdncentral.com/whats-network-functions-virtualization-nfv/
[130] http://www.sdncentral.com/which-is-better-sdn-or-nfv/
20
What is Virtualization?
101
102 What is Virtualization?
References
[131] http://www.businessnewsdaily.com/5791-virtualization-vs-cloud-
computing.html
[132] http://searchservervirtualization.techtarget.com/definition/virtualization
[133] http://www.vmware.com/virtualization
[134] http://www.wisegeek.com/what-are-the-benefits-of-virtualization.htm
[135] http://www.datacenterdynamics.com/focus/archive/2013/10/
future-virtualization
21
Risks of Cloud Computing
Explained (Both Sides)
105
106 Risks of Cloud Computing Explained (Both Sides)
by eliminating the need to build a costly data center and hire an IT team to
manage it.
Most businesses, however, have one major concern when it comes to
cloud computing: Exactly how safe is the cloud? Although most reputable
cloud providers have top-of-the-line security to protect users’ data, experts
say that there is no such thing as a completely safe cloud system.
Considering how far the cloud has come in recent years spurs questions
of what kind of risks are faced by businesses when using cloud computing,
the following list can help.
• Data integrity: If you think that your data security is questionable when
you store it on-site, imagine the risk when your data is being stored at a
location you do not even know.
• Virtualization: Practically every cloud service provider uses virtualiza-
tion. As a result, users do not only have to worry about the risks asso-
ciated with physical machines but also with the unique risks associated
with virtual server hosts and the guests that access them.
• Authentication, authorization, and access control: Your cloud vendor’s
choice of authentication, authorization, and access control mechanisms
is crucial, but a lot depends on process as well.
• Cyberattacks: Any time you store data on the internet, you are at the
risk for a cyberattack. This is particularly problematic on the cloud,
where volumes of data are stored by all types of users on the same cloud
system.
• Insider threats: Just as cyberattacks are on the rise, so are security
breaches from the inside. Once an employee gains or gives others access
to your cloud, everything from customer data to confidential informa-
tion and intellectual property are up for grabs.
• Government intrusion: With the recent NSA leaks and the ensuing
reports on government surveillance programs, competitors are not the
only ones who may want to take a peek at your data.
• Legal liability: Risks associated with the cloud are not limited to security
breaches. They also include its aftermath, such as lawsuits filed by or
against you. “The latest risks to using cloud for business are compliance,
legal liability and business continuity,” said Robert J. Scott, managing
partner of Scott & Scott LLP, an intellectual property and technology
law firm. “Data breach incidences are on the rise, and so are lawsuits.”
• Lack of standardization: A provider could have the latest security fea-
tures, but due to the general lack of cloud standardization, there are no
clear-cut guidelines unifying cloud providers [138].
For business using or considering migrating to the cloud, all you can do
is be as prepared as you can possibly be. The key is getting to know providers
as much as you can, both as a company and from an end-user perspective
[139, 140].
References
[136] http://www.businessnewsdaily.com/5215-dangers-cloud-computing.html
[137] http://www.liquidtechnology.net/blog/cloud-computing-security-
risks/
[138] http://www.pwc.com/us/en/issues/cloud-computing/risks.jhtml
[139] http://www.networkworld.com/article/2226230/cisco-subnet/security-
professionals-identify-it-risks-associated-with-cloud-computing.html
[140] http://www.infoworld.com/d/security/the-5-cloud-risks-you-have-
stop-ignoring-214696?page=0,1
22
Cloud-of-Clouds or (Intercloud)
109
110 Cloud-of-Clouds or (Intercloud)
of other clouds. This is analogous to the way the internet works, in that a
service provider, to which an endpoint is attached, will access or deliver traf-
fic from/to source/destination addresses outside of its service area by using
internet routing protocols with other service providers with whom it has a
pre-arranged exchange or peering relationship. It is also analogous to the way
mobile operators implement roaming and inter-carrier interoperability. Such
forms of cloud exchange, peering, or roaming may introduce new business
opportunities among cloud providers if they manage to go beyond the theo-
retical framework [142].
IBM researchers are working on a solution that they claim can seamlessly
store and move data across multiple cloud platforms in real time. The firm thinks
that the technology will help enterprises with service reliability concerns. On
top of this, they hope to “cloud-enable” almost any digital storage product.
Researchers at IBM have developed a “drag-and-drop” toolkit that allows
users to move file storage across almost any cloud platform. The company
cloud would host identity authentication and encryption technologies as well as
other security systems on an external cloud platform (the “InterCloud Store”)
to keep each cloud autonomous, while also keeping them synced together.
IBM’s Evangelos Eleftheriou explained that the cloud-of-clouds inven-
tion can help avoid service outrages due to the fact that it can tolerate crashes
of any number of clients. It would do this by using the independence of mul-
tiple clouds linked together to increase the overall reliability.
Storage services do not communicate directly with each other but
instead go through the larger cloud for authentication. Data is encrypted as
it leaves one station and decrypted before it reaches the next. If one cloud
happens to fail, a back-up cloud responds immediately.
The cloud-of-clouds is also intrinsically more secure: “If one provider
gets hacked there is little chance they will penetrate other systems at the same
time using the same vulnerability,” says Alessandro Sorniotti, cloud storage
scientist at IBM and one of the researchers. “From the client perspective, we
will have the most available and secure storage system.”
HP and RedHat have also made offerings of similar kinds, Cisco will
invest $1B in the next two years to build its expanded cloud business, and we
expect the incremental capabilities to expand the true investment figure even
further [143].
there will be tight integration between multiple clouds. This tighter integra-
tion of clouds will have practical implications for businesses, giving ana-
lysts the ability to sift through siloes of big data applications to make better
informed decisions, according to John Messina, a senior member with the
National Institute of Standards and Technology’s cloud computing program.
“Interoperability is much broader than an organization or consumers talking
with cloud providers, but also involves cloud providers communicating with
one another and those providers interconnecting with other resources such as
social media and sensor networks,” Messina said [144].
NIST along with other international groups such as the Institute of
Electrical and Electronics Engineers, the International Electrotechnical
Commission, the International Standards Organization, and the TM Forum
are pushing for interoperability and portability standards. “I think there is
a safe prediction that we will have much more interoperability in the future
right around the three- to five-year point. Probably closer to five, we will have
that cloud of cloud people are talking about,” Messina said [144].
Randy Garrett, program manager with the Defense Advanced Research
Projects Agency’s Information Innovation Office, who was also on the panel,
said, “We will see a growth in the Internet of Things,” referring to devices
ranging from smartphones to automated sensors and non-computing devices
connected to the internet.
An interconnected world has potential benefits, but it also creates new
risks. For example, 10 years ago, there was no danger that somebody could
remotely take over your car with a cyberattack. But a car today with onboard
computers, a GPS receiver, and wireless connections is vulnerable. Someone
can take over a car. They cannot steer it (unless we are talking about Google’s
driverless car), Garrett noted, but can do other things. “So when you take that
possibility and spread it out, it makes you wonder what type of future world
we will have if somebody can come in remotely change your heating or air
conditioning or shut down your car.”
“Still, a lot of future benefits will arise as a result of connected devices
and access to more information such as the better tracking of the rise and
spread of epidemics, a larger sampling of medicines or the ability to detect
manufacturing defects,” Garrett said [145].
References
[141] http://www.cloudcomputing-news.net/news/2013/dec/10/ibm-
launches-cloud-clouds-offering-aims-stop-vendor-lockin/
[142] http://www.techopedia.com/definition/7756/intercloud
112 Cloud-of-Clouds or (Intercloud)
[143] http://www.cloudwards.net/news/ibm-offers-intercloud-storage-2914/
[144] http://www.techradar.com/us/news/internet/ibm-working-on-cloud-
of-clouds-solution-to-limit-vendor-lock-in-1207375#null
[145] http://gcn.com/Articles/2013/05/31/Cloud-of-clouds-5-years-in-
future.aspx?Page=3#
23
Myths and Facts About Cloud Computing
113
114 Myths and Facts About Cloud Computing
Myth #7: Migrating into the cloud is more hassle than it is worth: If you work
in partnership with a trusted and experienced hosting provider, it is a seam-
less process. It can all happen very quickly with minimal downtime.
Myth #8: Cloud is not for mission-critical use: Cloud computing can be used
for all aspects of business including mission-critical applications for many
reasons including less downtime, and auto backup.
Myth #9: Cloud is virtualization: Virtualization is software that manipulates
hardware, while cloud computing refers to a service that results from that
manipulation.
Myth #10: I will be caught by vendor “lock in”: This is true only to the same
extent of on-premise, traditional software. There would be nothing to stop busi-
nesses building their own applications and deal with more than one vendor [141].
• The Internet of Things takes off: Look for the industrial internet (a.k.a.
the Internet of Things) to start transforming operations in few coming
years, as solutions combining intelligent machines, big data analytics,
and end-user applications begin to roll out across major industries.
Cloud computing platforms will play a big role in creating the next
generation of intelligent, software-defined machines that are operable
and controllable entirely from centralized, remote locations.
• Better identity management in the cloud: Cloud services offer accessi-
bility, convenience, high-power, and redundancy, but with cloud-based
applications taking over businesses, there is a need to rethink security
policies. Look for identity management solutions to bring new para-
digms of security to the cloud.
• More software-defined hardware: In order for servers, storage, and
networking equipment to behave like one big “machine,” where appli-
cations can assume massive scalability, the entire infrastructure must
be virtualized and centrally controllable, that is, software-defined.
Ultimately, this trend goes beyond SDN (software-defined networks)
to include every system in the data center. Advanced software control
schemes pioneered by public cloud providers will continue to trickle
down to the enterprise [143].
PART 5
Security
24
Zero-Day Vulnerability and Heuristic
Analysis
121
122 Zero-Day Vulnerability and Heuristic Analysis
scope of attack might be limited and the attacker can only cause minimal
damage while further threats are contained.
Furthermore, with a robust patch management and vulnerability scan-
ning system in place, the administrator will receive notification as soon as the
attack is made public and security companies implement vulnerability checks
for it. These two important software solutions allow the administrator to take
proactive action until a patch for that exploit is released. The administrator
will also be notified when the patch for the zero-day attack is made public,
thus minimizing the window of opportunity for an attack to take place.
The second option is to use a good antivirus solution. A zero-day attack
does not become public knowledge for a period of time, and during that
period, the antivirus program will not detect any file containing this specific
vulnerability by using standard pattern analysis techniques.
However, effective antivirus solutions do not rely solely on antivirus
definitions to detect threats. A good antivirus also uses a technique called
heuristics analysis. This technique does not only look for certain patterns
in a file, but it will also analyze what the file actually does during its normal
execution. Depending on the file’s behavior, the antivirus (AV) product may
then classify the file as a virus if suspicious behavior is detected. This tech-
nique can help to detect a zero-day threat even though no one knows of the
vulnerability’s existence [148].
While antivirus solutions that use heuristic analyses can be a great
weapon against zero-day malware, there is no guarantee that the malware
behavior will always be classified as malicious. However, when AV is cou-
pled with a strong patch management strategy, the administrator has a much
stronger defense against infection by zero-day threats.
Other techniques used for early detection are as follows:
• Use VPNs to protect the contents of individual transmissions
• Deploy an intrusion detection system (IDS) (e.g., stateful firewall)
• Introduce network access control to prevent rogue machines from gain-
ing access to the network, in technical terms; least privilege access (LPA)
• Lock down wireless access points and use a security scheme like Wi-Fi
protected access for maximum protection against wireless-based attacks
References
[146] http://internet-security-suite-review.toptenreviews.com/premium-
security-suites/what-is-heuristic-antivirus-detection-.html
[147] http://www.welivesecurity.com/2010/12/29/what-are-heuristics/
[148] http://www.gfi.com/blog/defending-zeroday-threats/
[149] http://www.techopedia.com/definition/27451/zero-day-threat
25
The Zero Trust Model
127
128 The Zero Trust Model
References
[150] http://www.securitymanagement.com/article/zero-trust-model-007894
[151] http://www.securityweek.com/steps-implementing-zero-trust-network
[152] http://spyders.ca/reduce-risk-by-adopting-a-zero-trust-modelapproach-
to-security/
[153] http://www.cymbel.com/zero-trust-recommendations/
[154] http://csrc.nist.gov/cyberframework/rfi_comments/040813_forrester_
research.pdf
[155] https://go.forrester.com/research/
26
Cloud Computing Security
131
132 Cloud Computing Security
The past few years were not great for cybersecurity; we saw a large number
of high-profile cyberattacks, including Uber, Deloitte, Equifax, and the now
infamous WannaCry ransomware attack. The frightening truth about increas-
ing cyberattacks is that most businesses and the cybersecurity industry itself
are not prepared. Despite the constant flow of security updates and patches,
the number of attacks continues to rise [156].
Beyond the lack of preparedness on the business level, the cybersecu-
rity workforce itself is also having an incredibly hard time keeping up with
demand. By 2021, there are estimated to be an astounding 3.5 million unfilled
cybersecurity positions worldwide; the current staff is overworked with an
average of 52 hours a week, not an ideal situation to keep up with non-stop
threats.
135
136 First Line of Defense for Cybersecurity
expect when a breach occurs. Test these plans for effectiveness. Do not wait
for an exploit to find a hole in the process.
27.2.6 IT infrastructure
A modern enterprise has just too many IT systems, spread across geographies.
Manual tracking of the health of these systems, even when they operate in a
highly integrated manner, poses massive challenges. For most businesses, the
only practical method of embracing advanced (and expensive) cybersecurity
technologies is to prioritize their IT systems and cover those that they deem
critical for business continuity. Currently, cybersecurity is reactive. That is to
say that in most cases, it helps alert IT staff about data breaches, identity theft,
suspicious applications, and suspicious activities. So, cybersecurity is cur-
rently more of an enabler of disaster management and mitigation. This leaves a
crucial question unanswered – what about not letting cybercrime happen at all?
References
[156] https://www.csoonline.com/article/3250086/data-protection/7-cyber-
security-trends-to-watch-out-for-in-2018.html
[157] https://gcn.com/articles/2018/01/05/ai-cybersecurity.aspx
[158] https://www.darkreading.com/threat-intelligence/ai-in-cybersecurity-
where-we-stand-and-where-we-need-to-go/a/d-id/1330787?
[159] https://www.itproportal.com/features/cyber-security-ai-is-almost-
here-but-where-does-that-leave-us-humans/
[160] https://www.linkedin.com/pulse/wake-up-call-iot-ahmed-banafa
28
Second Line of Defense for Cybersecurity:
Blockchain
AI as the first line of defense for cybersecurity, the goal was to keep the
cyber-criminals at bay, but in case they managed to get in and infiltrate the
network, we need to initiate the second line of defense – blockchain. With
the fact that cybercrime and cybersecurity attacks hardly seem to be out
of the news these days and the threat is growing globally. Nobody would
appear immune to malicious and offensive acts targeting computer networks,
infrastructures, and personal computer devices. Firms clearly must invest to
stay resilient. Gauging the exact size of cybercrime and putting a precise
143
144 Second Line of Defense for Cybersecurity
US dollar value on it is nonetheless tricky. But one thing we can be sure about
is that the number is big and probably larger than the statistics reveal [161].
The global figure for cyber breaches had been put at around $200 bil-
lion annually.
New blockchain platforms are stepping up to address security concerns
in the face of recent breaches. Since these platforms are not controlled by a
singular entity, they can help ease the concerns created by a spree of recent
breach disclosures. Services built on top of blockchain have the potential to
inspire renewed trust due to the transparency built into the technology.
Developments in blockchain have expanded beyond record-keeping
and cryptocurrencies. The integration of smart contract development in
blockchain platforms has ushered in a wider set of applications, including
cybersecurity.
By using blockchain, transaction details are kept both transparent and
secure. Blockchain’s decentralized and distributed network also helps busi-
nesses to avoid a single point of failure, making it difficult for malicious
parties to steal or tamper with business data.
Transactions in the blockchain can be audited and traced. In addition,
public blockchains rely on distributed network to run, thus eliminating a single
point of control. For attackers, it is much more difficult to attack a large num-
ber of peers distributed globally as opposed to a centralized data center [162].
ledgers, a new block is created. This block further stores a key that is cryp-
tographically created. This key becomes the unlocking key for the next record
that is to be stored onto the ledger. In this manner, the data is extremely secure.
Furthermore, the hashing feature of blockchain technology is one of its
underlying qualities that make it such a prominent technology. Using cryp-
tography and the hashing algorithm, blockchain technology converts the data
stored in our ledgers. This hash encrypts the data and stores it in such a lan-
guage that the data can only be decrypted using keys stored in the systems.
Other than cybersecurity, blockchain has many applications in several fields
that help in maintaining and securing data. The fields where this technol-
ogy is already showing its ability are finance, supply chain management, and
blockchain-enabled smart contracts.
28.2.1 Decentralization
Thanks to the peer-to-peer network, there is no need for third-party verifica-
tion, as any user can see network transactions.
146 Second Line of Defense for Cybersecurity
28.2.3 Confidentiality
The confidentiality of network members is high due to the public-key cryp-
tography that authenticates users and encrypts their transactions.
28.2.5 Sustainability
Blockchain technology has no single point of failure, which means that even
in the case of DDoS attacks, the system will operate as normal, thanks to
multiple copies of the ledger.
28.2.6 Integrity
The distributed ledger ensures the protection of data against modification or
destruction. Besides, the technology ensures the authenticity and irreversibil-
ity of completed transactions. Encrypted blocks contain immutable data that
is resistant to hacking.
28.2.7 Resilience
The peer-to-peer nature of the technology ensures that the network will oper-
ate round-the-clock even if some nodes are offline or under attack. In the
event of an attack, a company can make certain nodes redundant and operate
as usual.
28.2.10 Availability
There is no need to store your sensitive data in one place, as blockchain
technology allows you to have multiple copies of your data that are always
available to network users.
28.4 Conclusion
Blockchain’s decentralized approach to cybersecurity can be seen as a fresh
take on the issues that the industry faces today. The market could only use
more solutions to combat the threats of cyberattacks. And the use of block-
chain may yet address the vulnerabilities and limitations of current security
approaches and solutions.
Throwing constant pots of money at the problem and knee-jerk reac-
tions is not the answer. Firms need to sort out their governance, awareness,
and organizational culture and critically look at the business purpose and
processes before they invest in systems to combat cybercrime.
The roster of these new services provided by blockchain may be limited
for now, and, of course, they face incumbent players in the cybersecurity
space. But this only offers further opportunity for other ventures to cover
other key areas of cybersecurity. Blockchain also transcends borders and
nationalities, which should inspire trust in users. And, with the growth of
these new solutions, the industry may yet restore some of the public’s trust
they may have lost in the midst of all these issues.
Overall, blockchain technology is a breakthrough in cybersecurity, as it
can ensure the highest level of data confidentiality, availability, and security.
However, the complexity of the technology may cause difficulties with devel-
opment and real-world use.
References 149
References
[161] https://www.ibm.com/blogs/insights-on-business/government/
convergence-blockchain-cybersecurity/
[162] https://www.forbes.com/sites/rogeraitken/2017/11/13/new-
blockchain-platforms-emerge-to-fight-cybercrime-secure-the-
future/#25bdc5468adc
[163] http://www.technologyrecord.com/Article/cybersecurity-via-
blockchain-the-pros-and-cons-62035
[164] https://www.allerin.com/blog/blockchain-cybersecurity
29
Network Security Needs Big Data
There are two types of organizations now: those that have been breached and
those that just do not know it yet. As attacks have become too sophisticated
for signature-based detection, there is a need for solutions that quickly notice
anomalous and potentially dangerous behavior to prevent breaches or –
failing that – detect malicious behavior once a breach has occurred, and min-
imize its impact, as Neill Occhiogrosso mentioned in his excellent article
about this topic.
The second half of 2014 witnessed serious security incidents starting
with Heartbleed, Bash Bug (Shellshock) to the recent Poodle bug; add to
that the highly publicized security breaches at Target, Home Depot, K-Mart,
and Chase. This raises the old question or quest: can we ever have a perfect
secure network? The quick answer is “no”; but not too fast – there are ways to
minimize risks and lower vulnerabilities of computer networks to the lowest
possible level.
151
152 Network Security Needs Big Data
157
158 Blockchain Technology and COVID-19
What every country is doing now fighting this pandemic would have
been restricted to fewer countries and in a much smaller scale. The usage of
a blockchain to share the information early on might have saved the world a
lot of pain.
The world had not seen anything like COVID-19 pandemic before in
the recent history. Today, we need to take a hard look at the reporting infra-
structure available for communicable diseases, both technology and regu-
lations, and improve upon that, such that we do not need to face another
pandemic like this in the future [173].
with a verification that their contributions have been received to the victims.
Blockchain would enable transparency for the general public to understand
how their donations have been used and its progress [9].
References
[165] https://btcmanager.com/us-authorities-blockchain-covid-19-critical-
services/?q=/us-authorities-blockchain-covid-19-critical-services/&
[166] https://www.govtech.com/products/Blockchain-Emerges-as-Useful-
Tool-in-Fight-Against-Coronavirus.html
[167] https://www.expresscomputer.in/blockchain/could-blockchain-
be-the-solution-for-surveillance-and-reporting-of-the-covid-19-
pandemic/51670/
[168] https://www.ibm.com/blogs/blockchain/2020/03/mipasa-project-and-
ibm-blockchain-team-on-open-data-platform-to-support-covid-19-
response/
[169] https://mipasa.org/about/
[170] https://www.ledgerinsights.com/us-homeland-security-lists-
blockchain-as-covid-19-critical-service/
[171] https://www.pymnts.com/blockchain/bitcoin/2020/bitcoin-daily-who-
debuts-mipasa-blockchain-to-share-covid-19-data-coinbases-retail-
payments-portal-passes-200m-transactions-processed/
[172] https://www.rollcall.com/2020/03/31/blockchain-could-transform-
supply-chains-aid-in-covid-19-fight/
[173] https://www.blockchain-council.org/blockchain/how-blockchain-can-
solve-major-challenges-of-covid-19-faced-by-healthcare-sectors/
31
How Blockchain is Revolutionizing
Crowdfunding
163
164 How Blockchain is Revolutionizing Crowdfunding
funds and strains the fundraising process when startups are looking for
every single dollar to help.
2. Fine print rules and regulations: Not all platforms accept services as a
possible project and demand real tangible products; such a mindset crip-
ples innovation and narrows the horizon of new products and services.
3. DIY marketing and advertising: With few exceptions, crowdfunding
platforms will not help with spreading the word about new startups,
which means startups need to pay for marketing and advertising yet
another strain on limited funds available for them and take their focus
from innovation and creativity.
4. Scam startups: In some cases, startups turn up as scams and produce
nothing, leaving investors with empty hands and no way to get their
money back.
5. Intellectual property risk: In some cases, startups have no protection of
their IP, leaving them exposed to experience investors who can take the
idea and enter the market early with all the resources they have.
31.2 How Blockchain Helps Crowdfunding 165
References
[174] https://due.com/blog/a-new-era-of-crowdfunding-blockchain/
[175] https://www.disruptordaily.com/blockchain-use-cases-crowdfunding/
32
Blockchain Technology and Supply
Chain Management
Managing today’s supply chains is extremely complex. For many products, the
supply chain can span over hundreds of stages; multiple geographical (interna-
tional) locations and a multitude of invoices and payments have several individu-
als and entities involved, and extend over months of time. Due to the complexity
and lack of transparency of the current supply chains, there is high interest in
how blockchains might transform the supply chain and logistics industry [177].
This interest rose from the long list of issues with current supply chain
management (SCM) including the following [176]:
• Difficulty of tracking
• Lack of trust
• High costs: procurement costs, transportation costs, inventory costs,
and quality costs
• Globalization barriers
167
168 Blockchain Technology and Supply Chain Management
References
[176] https://blockgeeks.com/guides/Blockchain-and-supply-chain/
[177] https://www.forbes.com/sites/bernardmarr/2018/03/23/how-Blockchain-
will-transform-the-supply-chain-and-logistics-industry/#c7c357e5fecd
[178] https://consensys.net/Blockchain-use-cases/supply-chain-management/
[179] https://www.technologyreview.com/2017/01/05/5880/a-secure-model-
of-iot-with-blockchain/
PART 7
IoT
33
IoT and COVID-19
173
174 IoT and COVID-19
In the following, we summarize some of the areas where IoT will flour-
ish because of the COVID-19 impact.
immutable fashion. In this case, had there been a blockchain network where
WHO, Health Ministry of each country, and maybe even relevant nodal hos-
pitals of each country were connected, sharing real-time information, about
any new communicable disease, then the world might have woken up much
earlier. We might have seen travel restrictions given sooner, quarantining pol-
icies set sooner, and social distancing implemented faster. And maybe fewer
countries would have got impacted.
What every country is doing now fighting this pandemic would have
been restricted to fewer countries and on a much smaller scale. The usage of
a blockchain to share the information early on might have saved the world a
lot of pain and deaths. This is an area where IoT and blockchain converged,
with all the info. Coming from the sensors/nodes and traveling over available
networks to be processed in the cloud and presented via applications in the
hands of health workers and authorities, blockchain will secure the data all
the way [182].
medical care drives the healthcare centers to look up to the IoT solution pro-
viders for an effective approach to tackle diseases.
The Internet of Medical Things (IoMT) along with cloud technologies
and AI offer an opportunity to help healthcare professionals to monitor their
patients, access the data, and provide treatment from a remote location; this
is possible by using devices like smart thermometers, smart wearables, track
and trace apps, robots, and smart medical devices [181].
References
[180] https://futureiot.tech/analysts-say-covid-19-pandemic-will-spur-iot-
adoption/
[181] https://blog.infraspeak.com/iot-covid-19/
[182] https://www.bbvaopenmind.com/en/technology/digital-world/
blockchain-technology-and-covid-19/
34
IoT and 5G Convergence
The convergence of 5G and Internet of Things (IoT) is the next natural move
for two advance technologies built to make users live conveniently, easier,
and more productive. But before talking about how they will unite, we need
to understand each of the two technologies.
Simply defined, 5G is the next-generation cellular network compared to
4G, the current standard, which offers speeds ranging from 7 to 17 Mbps for
upload and from 12 to 36 Mbps for download; 5G transmission speeds may
be as high as 20 Gbps. Latency will also be close to 10% of 4G transmis-
sion, and the number of devices that can be connected scales up significantly
which warranted the convergence with IoT [183].
The Internet of Things (IoT) is an ecosystem of ever-increasing com-
plexity; a universe of connected things providing key physical data and further
177
178 IoT and 5G Convergence
each other in real time and exchange information. For example, smart homes
will have hundreds of devices connected in every possible way to make our
life more convenient and enjoyable with smart appliances, energy, and secu-
rity and entertainment devices. In the case of industrial plants, we are talking
about thousands of connected devices used for streamlining the manufac-
turing process and provide safety and security; in addition to the concept of
building a smart [186].
34.3.2 Industrial
The Industrial Internet of Things (IIoT) is a network of physical objects, sys-
tems, platforms, and applications that contain embedded technology to com-
municate and share intelligence with each other, the external environment,
and with people. The adoption of the IIoT is being enabled by the improved
availability and affordability of sensors, processors, and other technologies
that have helped facilitate capture of and access to real-time information.
5G will not only offer a more reliable network but would also deliver an
extremely secure network for industrial IoT by integrating security into the
core network architecture. Industrial facilities will be among the major users
of private 5G networks [187, 190].
34.3.3 Healthcare
The requirement for real-time networks will be achieved using 5G, which
will significantly transform the healthcare industry. Use cases include live
transmission of high-definition surgery videos that can be remotely moni-
tored. The concept of telemedicine with real-time and bigger bandwidth will
be a reality. IoT’s sensors will be more sophisticated to give more in-depth
medical information of patients on the fly; for example, a doctor can check
up and diagnose patients while they are on the emergency vehicle on the way
to the hospital saving minutes which can be the difference between life and
death. The 2020 pandemic taught us the significance of alternative channels
of seeing our doctor beside in person, and many startups created apps for
telemedicine services during that period. 5G will propel the use of such apps
and make our doctor visits more efficient and less time-consuming [187].
References
[183] https://davra.com/5g-internet-of-things/
[184] https://www.linkedin.com/pulse/iot-blockchain-challenges-risks-
ahmed-banafa/
[185] https://www.linkedin.com/pulse/three-major-challenges-facing-iot-
ahmed-banafa/
[186] https://appinventiv.com/blog/5g-and-iot-technology-use-cases/
182 IoT and 5G Convergence
[187] https://www.geospatialworld.net/blogs/how-5g-plays-important-role-
in-internet-of-things/
[188] https://www.linkedin.com/pulse/iot-standardization-implementation-
challenges-ahmed-banafa/
[189] https://www.linkedin.com/pulse/why-iot-needs-fog-computing-
ahmed-banafa/
[190] https://www.linkedin.com/pulse/industrial-internet-things-iiot-
challenges-benefits-ahmed-banafa/
[191] https://www.amazon.com/Secure-Smart-Internet-Things-IoT/dp/
8770220301/
PART 8
Wearable and Mobile Technology
35
The Smart Platform: Wearable Computing
Devices (WCD)
185
186 The Smart Platform
References
[192] http://www.computerworld.com/s/article/9245632/As_wearable_
devices_hit_the_market_apps_are_sure_to_follow
[193] http://www.neongoldfish.com/blog/social-media/the-advantages-and-
disadvantages-of-wearable-tech/#sthash.eij8N9WN.dpuf
[194] http://searchconsumerization.techtarget.com/opinion/Wearable-
computing-devices-could-have-enterprise-prospects
36
Your Smart Device Will Feel Your
Pain and Fear
What if your smart device could empathize with you? The evolving field
known as affective computing is likely to make it happen soon. Scientists and
engineers are developing systems and devices that can recognize, interpret,
process, and simulate human affects or emotions. It is an interdisciplinary
field spanning computer science, psychology, and cognitive science. While
its origins can be traced to longstanding philosophical enquiries into emo-
tion, a 1995 paper on affective computing by Rosalind Picard catalyzed mod-
ern progress [195].
The more smart devices we have in our lives, the more we are going to
want them to behave politely and be socially smart. We do not want them to
bother us with unimportant information or overload us with too much infor-
mation. That kind of common-sense reasoning requires an understanding of
our emotional state. We are starting to see such systems perform specific,
189
190 Your Smart Device Will Feel Your Pain and Fear
predefined functions, like changing in real time how you are presented with
the questions in a quiz or recommending a set of videos in an educational
program to fit the changing mood of students.
How can we make a device that responds appropriately to your emo-
tional state? Researchers are using sensors, microphones, and cameras
combined with software logic. A device with the ability to detect and appro-
priately respond to a user’s emotions and other stimuli could gather cues
from a variety of sources. Facial expressions, posture, gestures, speech, the
force or rhythm of key strokes, and the temperature changes of a hand on
a mouse can all potentially signify emotional changes that can be detected
and interpreted by a computer. A built-in camera, for example, may capture
images of a user. Speech, gesture, and facial recognition technologies are
being explored for affective computing applications [196].
Just looking at speech alone, a computer can observe innumerable vari-
ables that may indicate emotional reaction and variation. Among these are
a person’s rate of speaking, accent, pitch, pitch range, final lowering, stress
frequency, breathiness, brilliance, loudness, and discontinuities in the pattern
of pauses or pitch.
Gestures can also be used to detect emotional states, especially when
used in conjunction with speech and face recognition. Such gestures might
include simple reflexive responses, like lifting your shoulders when you do
not know the answer to a question. Or they could be complex and meaning-
ful, as when communicating with sign language.
A third approach is the monitoring of physiological signs. These might
include pulse and heart rate or minute contractions of facial muscles. Pulses
in blood volume can be monitored, as can what is known as galvanic skin
response. This area of research is still relatively new, but it is gaining momen-
tum and we are starting to see real products that implement the techniques.
Recognizing emotional information requires the extraction of mean-
ingful patterns from the gathered data. Some researchers are using machine
learning techniques to detect such patterns.
Detecting emotion in people is one thing. But work is also going into
computers that themselves show what appear to be emotions. Already in use
are systems that simulate emotions in automated telephone and online con-
versation agents to facilitate interactivity between human and machine.
There are many applications for affective computing. One is in educa-
tion. Such systems can help address one of the major drawbacks of online
learning versus in-classroom learning: the difficulty faced by teachers in
adapting pedagogical situations to the emotional state of students in the
classroom. In e-learning applications, affective computing can adjust the
Your Smart Device Will Feel Your Pain and Fear 191
online user are protected and well defined. It is easier said than done, but
clear guidelines of what, where, and who will use the data will make accep-
tance of hardware and software of affective computing faster without replac-
ing physical pain with mental pain of fear of privacy and security and safety
of our data [197].
References
[195] https://www.linkedin.com/pulse/20140424221437-246665791-
affective-computing/
[196] https://www.linkedin.com/pulse/20140730042327-246665791-your-
computer-will-feel-your-pain/
[197] https://explorerresearch.com/gsr-market-research/
37
Technology Under Your Skin: Three
Challenges of Microchip Implants
Technology continues to get closer to merge with our bodies, from the smart-
phones in our hands to the smartwatches on our wrists to earbuds. Now, it
is getting under our skin literally with a tiny microchip. A human microchip
implant is typically an identifying integrated circuit device or radio-frequency
identification (RFID) transponder encased in silicate glass and implanted in
the body of a human being. This type of subdermal implant usually contains
a unique ID number that can be linked to information contained in an external
database, such as personal identification, law enforcement, medical history,
medications, allergies, and contact information [203].
In Sweden, thousands have had microchips inserted into their hands.
The chips are designed to speed up users’ daily routines and make their lives
more convenient – accessing their homes, offices, and gyms is as easy as
swiping their hands against digital readers. Chips also can be used to store
193
194 Technology Under Your Skin
emergency contact details, social media profiles, or e-tickets for events and
rail journeys [199].
Advocates of the tiny chips say that they are safe and largely protected
from hacking, but scientists are raising privacy concerns around the kind of
personal health data that might be stored on the devices. Around the size
of a grain of rice, the chips typically are inserted into the skin just above
each user’s thumb, using a syringe similar to that used for giving vaccina-
tions. Implanting chips in humans has privacy and security implications that
go well beyond cameras in public places, facial recognition, tracking of our
locations, our driving habits, our spending histories, and even beyond own-
ership of your data, which poses great challenges for the acceptance of this
technology [198, 199].
To understand the big picture about this technology, you need to know
that the use of the chips is an extension of the concept of Internet of Things
(IoT), which is a universe of connected things that keep growing by the min-
ute with over 30 billion connected devices at the end of 2020 and 75 billion
devices by 2025. Just as the world begins to understand the many benefits
of the Internet of Things, but also learns about the “dark side” from “smart
everything,” including our connected cities, we are now looking at small
chips causing major new privacy challenges [198, 202, 204].
Like any new trend, in order for that trend to be accepted and become
main stream, it needs to overcome three challenges: technology, business,
and society (regulations and laws) Figure 37.1.
The first challenge is technology: which is advancing every day and the
chips are getting smaller and smarter; in the world of IoT, the chips are con-
sidered as the first element of a typical IoT system which consists of sensors,
networks, cloud, and applications. As a sensor, the chip touches upon your
hand, your heart, your brain, and the rest of your body – literally. This new
development is set to give a very different meaning to “hacking the body” or
biohacking. While cyber experts continue to worry about protecting critical
infrastructure and mitigating security risks that could harm the economy or
cause a loss of life, implanted chips also affect health but add in new dimen-
sions to the risks and threats of hacking of sensors as they are considered as
the weakest link in IoT systems [198].
The second challenge is business: there are many companies in this
field and the opportunities are huge with all aspects of replacing ID in stores,
offices, airports, and hospitals, just to mention a few. Also, chips will pro-
vide key physical data and further processing of that data in the cloud to
deliver business insights, new treatments, and better services – presents a
huge opportunity for many players in all types of businesses and industries in
private and public sectors [202].
Technology Under Your Skin 195
References
[198] https://www.govtech.com/blogs/lohrmann-on-cybersecurity/chip-
implants-the-next-big-privacy-debate.html
[199] https://www.npr.org/2018/10/22/658808705/thousands-of-swedes-
are-inserting-microchips-under-their-skin
[200] https://www.cnn.com/2020/09/18/business/jobs-robots-microchips-
cyborg/index.html
[201] https://www.thomasnet.com/insights/the-future-of-microchip-
implants-in-humans/
[202] https://www.linkedin.com/pulse/three-major-challenges-facing-
iot-ahmed-banafa/
[203] https://en.wikipedia.org/wiki/Microchip_implant_(human)
[204] https://www.linkedin.com/pulse/8-key-tech-trends-post-covid-19-
world-ahmed-banafa/
PART 9
Future Trends in Technology
38
The Metaverse: A Different Perspective
The term “metaverse” is a hot topic of conversation recently, with many tech
giants like Facebook and Microsoft staking claims. But what is the metaverse?
Author Neal Stephenson is credited with coining the term “metaverse”
in his 1992 science fiction novel “Snow Crash,” in which he envisioned
lifelike avatars who met in realistic 3D buildings and other virtual reality
environments. Similarly, metaverse in a technical sense is another name
of Internet of Everything (IoE), a concept started in the early 2000s which
led to Internet of Things and its applications, a scale down version of
IoE [205].
Since then, various developments have made mileposts on the way
toward a real metaverse, an online virtual world which incorporates aug-
mented reality (AR), virtual reality (VR), 3D holographic avatars, video,
and other means of communication. As the metaverse expands, it will offer
a hyper-real alternative world. But this description is like talking about
“Frontend” in apps development without explaining the “Backend” side of
the apps. To understand that side of this new Xverse, we need to look at
metaverse from a different perspective [206].
199
200 The Metaverse
range of products sold into various markets vertical and horizontal, an end-
less list of products and services [208].
For example, in e-commerce, the metaverse provides a whole new rev-
enue stream for digital goods in a synchronic way instead of the current tra-
ditional way of click and buy. In human resources (HR), significant training
resources will be done with virtual reality (VR) and augmented reality (AR)
that are overlaying instructions in a real-world environment and giving some-
body a step-by-step playbook on how to put complex machine together or
run a device or try a new product, all will be done with virtual objects at the
heart of the metaverse. While in sales/marketing, connecting with customers
virtually and sharing virtual experience of the product or service will be com-
mon similar to our virtual meetings during the past two years in the middle of
Covid, but the metaverse will make it more real and more productive [209].
Crypto products including NFTs will be the natives of the metaverse
adding another block to Web 3.0 Xverse.
But as devices/people get more connected and collect more data and the
metaverse is expanded at a speed higher than the speed of the real universe,
privacy and security concerns will increase too. How companies decide to
balance customer privacy with this wealth of metaverse data will be critical
for the future of the metaverse and, more importantly, customers’ trust of the
metaverse and any future Xverse versions [210].
References
[205] https://cointelegraph.com/news/new-tribes-of-the-metaverse-community-
owned-economies
[206] https://biv.com/article/2021/11/top-business-applications-metaverse
[207] https://www.usatoday.com/story/tech/2021/11/10/metaverse-what-is-
it-explained-facebook-microsoft-meta-vr/6337635001/
[208] http://www.cisco.com/web/about/ac79/innov/IoE.html
[209] http://internetofeverything.cisco.com/
[210] http://www.cisco.com/web/solutions/trends/iot/overview.html
39
The Metaverse: Myths and Facts
203
204 The Metaverse
said, there are plenty of misconceptions about the metaverse, and here are a
few [216].
39.1.4 Myth #4: The metaverse will replace the real world
No, this is not the “Matrix”; the metaverse will not replace the real world. It
will be additive to the real world, an expansive virtual environment where you
39.1 Myths about the Metaverse 205
can do any number of different things: work, socialize, play, create, explore,
and more [214] Figure 39.1.
with customers virtually and sharing the virtual experience of the product or
service will be common similar to our virtual meetings during the past two
years in the middle of Covid, but the metaverse will make it more real and
more productive.
Finally, similarly to cloud computing, we will have private-metaverse,
hybrid-metaverse, and public-metaverse with all possible applications and
services in each type. Companies will benefit from all options based on
their capabilities and needs. The main goal here is to reach metaverse as a
service (MaaS) and add a label of “Metaverse Certified” on products and
services [211].
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[211] https://www.bbntimes.com/science/the-Metaverse-a-different-
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[212] https://www.mckinsey.com/industries/retail/our-insights/probing-
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[213] https://venturebeat.com/2022/03/24/5-common-Metaverse-
misconceptions/
[214] https://www.mckinsey.com/industries/retail/our-insights/probing-
reality-and-myth-in-the-Metaverse
[215] https://jarnoduursma.com/blog/7-misconceptions-about-the-Metaverse/
[216] https://analyticsindiamag.com/m isconceptions-about-Metaverse-
mark-zuckerberg-virtual-reality-augmented-real-world-gaming/
40
Eight Key Tech Trends in a Post-COVID-19
World
209
210 Eight Key Tech Trends in a Post-COVID-19 World
extremely valuable as companies confront and adapt to the next normal once
this pandemic subsides [218].
AI will increasingly contribute to the forecasting of consumers’ behav-
ior, which became hardly predictable, and to help businesses organize
effective logistics. Chatbots may provide clients’ support 24/7, one of the
“must-haves” during the lockdown [219].
40.3 VR/AR
This pandemic increased the number of people using VR headsets to play
video games, explore virtual travel destinations, and partake in online enter-
tainment; as they isolate at home, they are also using this technology to seek
human interaction through social VR platforms.
Businesses have also been experimenting with VR platforms to train
employees, hold conferences, collaborate on projects, and connect employ-
ees virtually. For example, scientists worldwide have turned to VR platform
for molecular design, to collaborate on coronavirus research and potential
treatments. Now that businesses and consumers know the extent to which
this technology can be used, we are likely to see more virtual conferences and
human interactions as our new normal sets in [218].
40.4 5G Networks
5G is acknowledged as the future of communication and the cutting edge for
the entire mobile industry. Deployment of 5G networks will emerge between
212 Eight Key Tech Trends in a Post-COVID-19 World
IoT also fuels edge computing; thus, data storage and computation
become closer to the points of action, enabling saves in bandwidth and
low latency. IoT will transform the user experience profoundly, provid-
ing opportunities that were not possible before. Gaining this experience
may be forced by the pandemic, when people are spending almost all their
time at home. IoT devices that make life quality better and daily life more
comfortable can become quite trendy. For example, telemedicine and IoT
devices helping to monitor people’s health indicators may increase their
popularity [219].
40.7 Cybersecurity
Cybersecurity is one of the vital technologies for organizations, especially
whose business processes are based on data-driven technologies. Much more
attention is being paid to privacy and data protection since the European
Union’s General Data Protection Regulations (GDRP) has been signed, and
recently CCPA in California.
During COVID-19 pandemic lockdown, when thousands of people
are forced to work remotely, volumes of private data may become totally
vulnerable or at least not protected in a proper way. This emerging chal-
lenge may give another incentive to the implementation of cybersecurity
practices. Cybercriminals took advantage of the fear factor of this virus to
send their own viruses; there are many examples of such activities recently
including fake domains of COVID-19, phishing emails promising virus pro-
tection kits, and even info about canceled summer Olympic games. In addi-
tion, there is an increase in ransomware attacks on health institutions and
even hacking of research centers to steal any info about possible vaccine of
COVID-19 [219].
supporting efforts around the globe to battle the virus as explained in the
following list [220]:
1. Tracking infectious disease outbreaks
2. Donations tracking
3. Crisis management
4. Securing medical supply chains
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224 References
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[172] https://www.rollcall.com/2020/03/31/blockchain-could-transform-
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[173] https://www.blockchain-council.org/blockchain/how-blockchain-can-
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[174] https://due.com/blog/a-new-era-of-crowdfunding-blockchain/
[175] https://www.disruptordaily.com/blockchain-use-cases-crowdfunding/
[176] https://blockgeeks.com/guides/Blockchain-and-supply-chain/
[177] https://www.forbes.com/sites/bernardmarr/2018/03/23/how-Blockchain-
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[178] https://consensys.net/Blockchain-use-cases/supply-chain-management/
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[180] https://futureiot.tech/analysts-say-covid-19-pandemic-will-spur-iot-
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[181] https://blog.infraspeak.com/iot-covid-19/
[182] https://www.bbvaopenmind.com/en/technology/digital-world/
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[183] https://davra.com/5g-internet-of-things/
[184] https://www.linkedin.com/pulse/iot-blockchain-challenges-risks-
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[185] https://www.linkedin.com/pulse/three-major-challenges-facing-iot-
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[186] https://appinventiv.com/blog/5g-and-iot-technology-use-cases/
[187] https://www.geospatialworld.net/blogs/how-5g-plays-important-role-
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[188] https://www.linkedin.com/pulse/iot-standardization-implementation-
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[189] https://www.linkedin.com/pulse/why-iot-needs-fog-computing-
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[190] https://www.linkedin.com/pulse/industrial-internet-things-iiot-
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[191] https://www.amazon.com/Secure-Smart-Internet-Things-IoT/dp/
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Index
A C
Adaptability challenges 148 CDN 91–96
Affective Computing 49–51, 62, Chatbot 211
189–192 Cloud Computing 55, 79, 81, 84,
AI 31–32, 34–35, 42, 45–47, 60, 101, 103, 105–107, 109, 111,
135–141, 143, 149, 176, 178, 113–117, 128, 131–133, 152,
210–211 180, 208, 211
Apps 69, 74, 95, 176, 181, 185, Complexity 22, 24, 66, 76, 102,
199, 211 148, 167, 177
Artificial Intelligence 24, 31, 45, Confidentiality 132, 146, 148
54, 149, 210 Connectivity 178, 180, 186, 212
Authentication 22, 24, 75, 107, 110, Content Delivery Networks 91
153 COVID-19 24, 33, 59, 62, 157–161,
Automotive 89, 180 173–176, 196, 209–215
Autonomic Computing 53–55 Crisis Management 160, 214–215
Crowdfunding 163–166
B CRQC 40–41
Bandwidth 83, 92, 94–95, 102, 106, Cryptocurrency 22
178, 181, 212–213 Cryptographically Relevant
Big Data 57, 59–62, 65–67, 69–73, Quantum Computers 41
75, 81–82, 89, 111, 115–117, Cryptography 9–11, 15–16, 23–24,
151, 153–154, 195 28–30, 39–41, 145–146, 148, 169
Big Data Analytics 70, 115, 117, Customer Trust 147
153–154 Cybersecurity 135–136, 138–141,
Bitcoin 22, 28, 30, 161 143–145, 147–149, 195–196, 213
Blockchain 25, 27–29, 34,
143–149, 155, 157–161, 163, D
165–169, 174–176, 181, Dark Data 57, 65–67
213–215 Data Analysis 73, 154, 178
227
228 Index
Data Center 82, 99, 106, 117, 144 Implementation 22, 136, 149, 153,
Data Lake 73–77 174, 180, 182, 211, 213
Data quality 75, 146 Industrial 81, 89, 117, 179–182
Decentralized 72, 144, 148 Industrial Internet of Things 117,
Deep Learning 45–47 181
Digital Transformation 209 Infectious Disease 159, 214
Distributed Ledger 146, 160 Information Technology 45, 128,
152
E Integrity 54, 89, 107, 132, 146
E-Commerce 91, 175, 180, 201, Internet of Everything 55, 87–89,
207 199
Edge Computing 81–84, 180, 213 Internet of Things 84, 87–88, 111,
Encryption 10–11, 15, 22–23, 115, 117, 139, 173, 177, 181,
27–30, 75, 110, 133 194, 199, 212
Entanglement 6, 18, 28, 39–40 Internet Protocol 124, 137, 164, 212
Interoperability 110–111, 180, 204,
F 206
Fog Computing 1 IoE 55, 87–90, 199, 201
Fraud security 146 IoT 21–22, 24–25, 74, 84–85,
87–90, 115, 139, 141, 169, 171,
G 173–182, 194–196, 201, 212–213
gaming 204, 208 IoT Security 139
Gateways 13, 19, 84, 98 IP 124, 137, 164, 212
Irreversibility 146–147
H IT infrastructure 140
Hash function 28
Healthcare 14, 19, 21, 33, 89, 157, L
161, 175–176, 179, 181, 213 Latency 81–84, 92, 95, 177, 179,
Heuristic Analysis 121, 125 213
High operation costs 148 Logical Qubits 38–41
Hubs 13, 19, 212
Human 18, 45–47, 49–51, 53–55, M
60, 62, 132, 136, 141, 169, Medical Supply Chains 160,
189–191, 193, 195–196, 201, 214–215
207, 209–211 Metaverse 81–82, 84, 191,
Hyperledger 160 199–201, 203–208
Microchip 193, 195–196
I Mirai 139
IIoT 181–182 Mobile Technology 183
Index 229
231