research-article

Public Access

Secure data types: a simple abstraction for confidentiality-preserving data analytics

Authors:

Savvas Savvides,

Julian James Stephen,

Masoud Saeida Ardekani,

Vinaitheerthan Sundaram,

Patrick EugsterAuthors Info & Claims

SoCC '17: Proceedings of the 2017 Symposium on Cloud Computing

Pages 479 - 492

https://doi.org/10.1145/3127479.3129256

Published: 24 September 2017 Publication History

Abstract

Cloud computing offers a cost-efficient data analytics platform. However, due to the sensitive nature of data, many organizations are reluctant to analyze their data in public clouds. Both software-based and hardware-based solutions have been proposed to address the stalemate, yet all have substantial limitations. We observe that a main issue cutting across all solutions is that they attempt to support confidentiality in data queries in a way transparent to queries. We propose the novel abstraction of secure data types with corresponding annotations for programmers to conveniently denote constraints relevant to security. These abstractions are leveraged by novel compilation techniques in our system Cuttlefish to compute data analytics queries in public cloud infrastructures while keeping sensitive data confidential. Cuttlefish encrypts all sensitive data residing in the cloud and employs partially homomorphic encryption schemes to perform operations securely, resorting however to client-side completion, re-encryption, or secure hardware-based re-encryption based on Intel's SGX when available based on a novel planner engine. Our evaluation shows that our prototype can execute all queries in standard benchmarks such as TPC-H and TPC-DS with an average overhead of 2.34× and 1.69× respectively compared to a plaintext execution that reveals all data.

References

[1]

Apache Pig. http://pig.apache.org.

[2]

BigDigits multiple-precision arithmetic library. http://www.di-mgt.com.au/bigdigits.html.

[3]

Intel SGX. https://software.intel.com/en-us/isa-extensions/intel-sgx.

[4]

SGX Virtualization. https://01.org/intel-software-guard-extensions/sgx-virtualization.

[5]

2014. Intel Software Guard Extensions Programming Reference. (2014). https://software.intel.com/sites/default/files/managed/48/88/329298-002.pdf.

[6]

2014. Synopsys, Inc., Open Source Report 2014. (2014). http://go.coverity.com/rs/157-LQW-289/images/2014-Coverity-Scan-Report.pdf.

[7]

George J Annas. 2003. HIPAA regulations-a new era of medical-record privacy? New England Journal of Medicine 348, 15 (2003), 1486--1490.

[8]

Arvind Arasu, Spyros Blanas, Ken Eguro, Raghav Kaushik, Donald Kossmann, Ravishankar Ramamurthy, and Ramarathnam Venkatesan. 2013. Orthogonal Security with Cipherbase. In Biennial Conf. on Innovative DataSystems Research (CIDR).

[9]

Alessandro Armando, Roberto Carbone, Luca Compagna, Jorge Cuellar, and Llanos Tobarra. 2008. Formal Analysis of SAML 2.0 Web Browser Single Sign-on: Breaking the SAML-based Single Sign-on for Google Apps. In W. on Formal Methods in Security Engineering (FMSE). 1--10.

[10]

Sergei Arnautov, Bohdan Trach, Franz Gregor, Thomas Knauth, Andre Martin, Christian Priebe, Joshua Lind, Divya Muthukumaran, Dan O'Keefe, Mark L Stillwell, David Goltzsche, Dave Eyers, Rüdiger Kapitza, Peter Pietzuch, and Christof Fetzer. 2016. SCONE: Secure Linux Containers with Intel SGX. In Symp. on Op. Sys. Design and Implementation (OSDI). 689--703.

[11]

Sumeet Bajaj and Radu Sion. 2014. TrustedDB: A Trusted Hardware-Based Database with Privacy and Data Confidentiality. IEEE Trans. Knowl. Data Eng. 26, 3 (2014), 752--765.

Digital Library

[12]

Andrew Baumann, Marcus Peinado, and Galen C. Hunt. 2014. Shielding Applications from an Untrusted Cloud with Haven. In Symp. on Op. Sys. Design and Implementation (OSDI). 267--283.

[13]

Dan Boneh Ben A. Fisch, Dhinakaran Vinayagamurthy and Sergey Gorbunov. 2016. Iron: Functional Encryption using Intel SGX. Cryptology ePrint Archive, Report 2016/1071. (2016). http://eprint.iacr.org/2016/1071.

[14]

Alexandra Boldyreva, Nathan Chenette, Younho Lee, and Adam O'Neill. 2009. Order-Preserving Symmetric Encryption. In Int. Conf. on The Theory and Applications of Cryptographic Techniques (EUROCRYPT). 224--241.

[15]

Alexandra Boldyreva, Nathan Chenette, and Adam O'Neill. 2011. Order-preserving Encryption Revisited: Improved Security Analysis and Alternative Solutions. In Annual Int. Cryptology Conf. (CRYPTO). Springer-Verlag, 578--595.

[16]

Dan Boneh, Kevin Lewi, Mariana Raykova, Amit Sahai, Mark Zhandry, and Joe Zimmerman. 2015. Semantically Secure Order-Revealing Encryption: Multi-input Functional Encryption Without Obfuscation. In Int. Conf. on The Theory and Applications of Cryptographic Techniques (EUROCRYPT). 563--594.

[17]

Stefan Brenner, Colin Wulf, Matthias Lorenz, Nico Weichbrodt, David Goltzsche, Christof Fetzer, Peter Pietzuch, and Rüdiger Kapitza. 2016. SecureKeeper: Confidential ZooKeeper using Intel SGX. In Int. Conf. on Middleware (MIDDLEWARE). 14:1--14:13.

Digital Library

[18]

Florian Cajori. 1911. Horner's method of approximation anticipated by Ruffini. Bull. Amer. Math. Soc. 17, 8 (05 1911), 409--414.

[19]

Nathan Chenette, Kevin Lewi, Stephen A. Weis, and David J. Wu. 2016. Practical Order-Revealing Encryption with Limited Leakage. In Int. Conf. on Fast Software Encryption (FSE) (FSE 2016). 474--493.

[20]

Cloudera. A TPC-DS like benchmark for Cloudera Impala. https://github.com/cloudera/impala-tpcds-kit.

[21]

Sashank Dara and Scott R. Fluhrer. 2014. FNR: Arbitrary Length Small Domain Block Cipher Proposal. In Int. Conf. on Security, Privacy, and Applied Cryptography Engineering (SPACE). 146--154.

[22]

Rowan Davies. 2005. Practical Refinement-type Checking. Ph.D. Dissertation. AAI3168521.

Digital Library

[23]

Dorothy E. Denning. 1976. A Lattice Model of Secure Information Flow. Commun. ACM (1976), 236--243.

[24]

Dorothy E. Denning and Peter J. Denning. 1977. Certification of Programs for Secure Information Flow. Commun. ACM (1977), 504--513.

[25]

T. ElGamal. 1985. A Public-Key Cryptosystem and a Signature Scheme Based on Discrete Logarithms. Trans. on Information Theory 31, 4 (1985), 469--472.

Digital Library

[26]

Sky Faber, Stanislaw Jarecki, Hugo Krawczyk, Quan Nguyen, Marcel-Catalin Rosu, and Michael Steiner. 2015. Rich Queries on Encrypted Data: Beyond Exact Matches. In Symp. on Research in Computer Security (ESORICS). 123--145.

[27]

Tim Freeman and Frank Pfenning. 1991. Refinement Types for ML. In Conf. on Prog. Lang. Design and Implementation (PLDI). ACM, 268--277.

[28]

Craig Gentry. 2009. A Fully Homomorphic Encryption Scheme. Ph.D. Dissertation. Advisor(s) Boneh, Dan. AAI3382729.

[29]

Craig Gentry, Shai Halevi, and Nigel P. Smart. 2012. Homomorphic Evaluation of the AES Circuit. IACR Cryptology ePrint Archive (2012). Informal publication.

Digital Library

[30]

Paul Grubbs, Kevin Sekniqi, Vincent Bindschaedler, Muhammad Naveed, and Thomas Ristenpart. 2017. Leakage-Abuse Attacks against Order-Revealing Encryption. In Symp. on Security and Privacy (S&P). 655--672.

[31]

Hakan Hacigümüs, Balakrishna R. Iyer, Chen Li, and Sharad Mehrotra. 2002. Executing SQL over encrypted data in the database-service-provider model. In Int. Conf. on the Mgt. of Data (SIGMOD). 216--227.

[32]

Alon Y. Halevy. 2001. Answering Queries Using Views: A Survey. The VLDB Journal 270--294.

[33]

A. Hosangadi, F. Fallah, and R. Kastner. 2006. Optimizing Polynomial Expressions by Algebraic Factorization and Common Subexpression Elimination. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2006), 2012--2022.

[34]

Florian Kerschbaum. 2015. Frequency-Hiding Order-Preserving Encryption. In Int. Conf. on on Computer and Communications Security (CCS). ACM, 656--667.

[35]

Chang Lan, Justine Sherry, Raluca Ada Popa, Sylvia Ratnasamy, and Zhi Liu. 2016. Embark: Securely Outsourcing Middleboxes to the Cloud. In Networked Sys. Design and Implem. (NSDI). 255--273.

Digital Library

[36]

Kevin Lewi and David J. Wu. 2016. Order-Revealing Encryption: New Constructions, Applications, and Lower Bounds. In Int. Conf. on on Computer and Communications Security (CCS). 1167--1178.

[37]

Frank McKeen, Ilya Alexandrovich, Alex Berenzon, Carlos V. Rozas, Hisham Shafi, Vedvyas Shanbhogue, and Uday R. Savagaonkar. 2013. Innovative instructions and software model for isolated execution. In W. on Hardware and Architectural Support for Security and Privacy (HASP). 10.

[38]

Muhammad Naveed, Seny Kamara, and Charles V. Wright. 2015. Inference Attacks on Property-Preserving Encrypted Databases. In Int. Conf. on on Computer and Communications Security (CCS). ACM, 644--655.

[39]

Christopher Olston, Benjamin Reed, Utkarsh Srivastava, Ravi Kumar, and Andrew Tomkins. 2008. Pig Latin: A Not-so-foreign Language for Data Processing. In Int. Conf. on the Mgt. of Data (SIGMOD). 1099--1110.

Digital Library

[40]

Kay Ousterhout, Ryan Rasti, Sylvia Ratnasamy, Scott Shenker, and Byung-Gon Chun. 2015. Making Sense of Performance in Data Analytics Frameworks. In Networked Sys. Design and Implem. (NSDI). 293--307.

[41]

Pascal Paillier. 1999. Public-key Cryptosystems Based on Composite Degree Residuosity Classes. In Int. Conf. on The Theory and Applications of Cryptographic Techniques (EUROCRYPT). 223--238.

[42]

Antonis Papadimitriou, Ranjita Bhagwan, Nishanth Chandran, Ramachandran Ramjee, Andreas Haeberlen, Harmeet Singh, Abhishek Modi, and Saikrishna Badrinarayanan. 2016. Big Data Analytics over Encrypted Datasets with Seabed. In Symp. on Op. Sys. Design and Implementation (OSDI).

[43]

Raluca Ada Popa, Frank H. Li, and Nickolai Zeldovich. 2013. An Ideal-Security Protocol for Order-Preserving Encoding. In Symp. on Security and Privacy (S&P). 463--477.

[44]

Raluca Ada Popa, Catherine M. S. Redfield, Nickolai Zeldovich, and Hari Balakrishnan. 2011. Cryptdb: protecting confidentiality with encrypted query processing. In Symp. on Op. Sys. Principles (SOSP). 85--100.

Digital Library

[45]

Thomas Ristenpart and Eran Tromer. 2009. Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds. In Int. Conf. on on Computer and Communications Security (CCS). 199--212.

Digital Library

[46]

Hossein Shafagh, Anwar Hithnawi, Andreas Droscher, Simon Duquennoy, and Wen Hu. 2015. Talos: Encrypted Query Processing for the Internet of Things. In Conf. on Embedded Networked Sensor Sys. (SenSys).

[47]

Justine Sherry, Chang Lan, Raluca Ada Popa, and Sylvia Ratnasamy. 2015. BlindBox: Deep Packet Inspection over Encrypted Traffic. In Int. Conf. on Data Communication (SIGCOMM). 213--226.

Digital Library

[48]

Dawn Xiaodong Song, David Wagner, and Adrian Perrig. 2000. Practical Techniques for Searches on Encrypted Data. In Symp. on Security and Privacy (S&P). 44--55.

[49]

Julian James Stephen, Savvas Savvides, Russell Seidel, and Patrick Eugster. 2014. Practical Confidentiality Preserving Big Data Analysis. In W. on Hot Topics in Cloud Computing (HotCloud).

[50]

Julian James Stephen, Savvas Savvides, Russell Seidel, and Patrick Th. Eugster. 2014. Program analysis for secure big data processing. In Int. Conf. on Automated Software Engineering (ASE). 277--288.

[51]

Julian James Stephen, Savvas Savvides, Vinaitheerthan Sundaram, Masoud Saeida Ardekani, and Patrick Eugster. 2016. STYX: Stream Processing with Trustworthy Cloud-based Execution. In Symp. on Cloud Computing (SoCC). 348--360.

[52]

Sai Deep Tetali, Mohsen Lesani, Rupak Majumdar, and Todd D. Millstein. 2013. Mr-Crypt: Static analysis for secure cloud computations. In Conf. on Object-Oriented Prog. Sys., Lang. and Applications (OOPSLA). 271--286.

[53]

Stephen Tu, M. Frans Kaashoek, Samuel Madden, and Nickolai Zeldovich. 2013. Processing Analytical Queries over Encrypted Data. Proc. VLDB Endow. 6, 5 (2013), 289--300.

Digital Library

[54]

Abhishek Verma, Ludmila Cherkasova, and Roy H. Campbell. 2011. ARIA: Automatic Resource Inference and Allocation for Mapreduce Environments. In Int. Conf. on Autonomic Computing (ICAC). 235--244.

[55]

Dennis M. Volpano, Cynthia E. Irvine, and Geoffrey Smith. 1996. A Sound Type System for Secure Flow Analysis. Journal of Computer Security 167--188.

[56]

Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauly, Michael J. Franklin, Scott Shenker, and Ion Stoica. 2012. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. In Networked Sys. Design and Implem. (NSDI). 15--28.

[57]

Wenting Zheng, Ankur Dave, Jethro G. Beekman, Raluca Ada Popa, Joseph E. Gonzalez, and Ion Stoica. 2017. Opaque: An Oblivious and Encrypted Distributed Analytics Platform. In Networked Sys. Design and Implem. (NSDI). 283--298.

Cited By

Mangipudi SChuprikov PEugster PViering MSavvides S(2023)Generalized Policy-Based Noninterference for Efficient Confidentiality-PreservationProceedings of the ACM on Programming Languages10.1145/35912317:PLDI(267-291)Online publication date: 6-Jun-2023
https://dl.acm.org/doi/10.1145/3591231
Wu YChen L(2023)Structured encryption for triangle counting on graph dataFuture Generation Computer Systems10.1016/j.future.2023.03.030145(200-210)Online publication date: Aug-2023
https://doi.org/10.1016/j.future.2023.03.030
Savvides SKhandelwal DEugster P(2020)Efficient confidentiality-preserving data analytics over symmetrically encrypted datasetsProceedings of the VLDB Endowment10.14778/3389133.338914413:8(1290-1303)Online publication date: 3-May-2020
https://dl.acm.org/doi/10.14778/3389133.3389144
Show More Cited By

Index Terms

Secure data types: a simple abstraction for confidentiality-preserving data analytics
1. Security and privacy
  1. Database and storage security
    1. Management and querying of encrypted data
  2. Systems security
    1. Distributed systems security

Recommendations

Efficient information-theoretically secure schemes for cloud data outsourcing
Abstract
Nowadays, outsourcing sensitive data to the cloud becomes popular. Outsourcing sensitive data to the cloud raises confidentiality concerns due to the loss of data control by the data owner. Data must be encrypted before outsourcing to ensure data ...
An efficient and secure data sharing framework using homomorphic encryption in the cloud
Cloud-I '12: Proceedings of the 1st International Workshop on Cloud Intelligence

Due to cost-efficiency and less hands-on management, data owners are outsourcing their data to the cloud which can provide access to the data as a service. However, by outsourcing their data to the cloud, the data owners lose control over their data as ...
Toward Secure Multikeyword Top-k Retrieval over Encrypted Cloud Data

Cloud computing has emerging as a promising pattern for data outsourcing and high-quality data services. However, concerns of sensitive information on cloud potentially causes privacy problems. Data encryption protects data security to some extent, but ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

SoCC '17: Proceedings of the 2017 Symposium on Cloud Computing

September 2017

672 pages

ISBN:9781450350280

DOI:10.1145/3127479

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 September 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Conference

SoCC '17

Sponsor:

SoCC '17: ACM Symposium on Cloud Computing

September 24 - 27, 2017

California, Santa Clara

Acceptance Rates

Overall Acceptance Rate 169 of 722 submissions, 23%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
751
Total Downloads

Downloads (Last 12 months)118
Downloads (Last 6 weeks)13

Reflects downloads up to 26 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Mangipudi SChuprikov PEugster PViering MSavvides S(2023)Generalized Policy-Based Noninterference for Efficient Confidentiality-PreservationProceedings of the ACM on Programming Languages10.1145/35912317:PLDI(267-291)Online publication date: 6-Jun-2023
https://dl.acm.org/doi/10.1145/3591231
Wu YChen L(2023)Structured encryption for triangle counting on graph dataFuture Generation Computer Systems10.1016/j.future.2023.03.030145(200-210)Online publication date: Aug-2023
https://doi.org/10.1016/j.future.2023.03.030
Savvides SKhandelwal DEugster P(2020)Efficient confidentiality-preserving data analytics over symmetrically encrypted datasetsProceedings of the VLDB Endowment10.14778/3389133.338914413:8(1290-1303)Online publication date: 3-May-2020
https://dl.acm.org/doi/10.14778/3389133.3389144
Eugster PKumar SSavvides SStephen J(2019)Ensuring Confidentiality in the Cloud of ThingsIEEE Pervasive Computing10.1109/MPRV.2018.287728618:1(10-18)Online publication date: 2-May-2019
https://dl.acm.org/doi/10.1109/MPRV.2018.2877286
Alowayed YCanini MMarcos PChiesa MBarcellos M(2018)Picking a PartnerProceedings of the 2018 Applied Networking Research Workshop10.1145/3232755.3232785(33-39)Online publication date: 16-Jul-2018
https://dl.acm.org/doi/10.1145/3232755.3232785
Ulybyshev DOqab Alsalem ABhargava BSavvides SMani GBen Othmane L(2018)Secure Data Communication in Autonomous V2X Systems2018 IEEE International Congress on Internet of Things (ICIOT)10.1109/ICIOT.2018.00029(156-163)Online publication date: Jul-2018
https://doi.org/10.1109/ICIOT.2018.00029

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents