research-article

Robotics cyber security: vulnerabilities, attacks, countermeasures, and recommendations

Authors:

Jean-Paul A. Yaacoub,

Hassan N. Noura,

Ali ChehabAuthors Info & Claims

International Journal of Information Security, Volume 21, Issue 1

Pages 115 - 158

https://doi.org/10.1007/s10207-021-00545-8

Published: 01 February 2022 Publication History

Abstract

The recent digital revolution led robots to become integrated more than ever into different domains such as agricultural, medical, industrial, military, police (law enforcement), and logistics. Robots are devoted to serve, facilitate, and enhance the human life. However, many incidents have been occurring, leading to serious injuries and devastating impacts such as the unnecessary loss of human lives. Unintended accidents will always take place, but the ones caused by malicious attacks represent a very challenging issue. This includes maliciously hijacking and controlling robots and causing serious economic and financial losses. This paper reviews the main security vulnerabilities, threats, risks, and their impacts, and the main security attacks within the robotics domain. In this context, different approaches and recommendations are presented in order to enhance and improve the security level of robotic systems such as multi-factor device/user authentication schemes, in addition to multi-factor cryptographic algorithms. We also review the recently presented security solutions for robotic systems.

References

[1]

Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., Harnisch, M.: Industry 4.0: the future of productivity and growth in manufacturing industries. Boston Consult. Group 9(1), 54–89 (2015)

[2]

Bahrin, M.A.K., Othman, M.F., Nor Azli, N.H., Talib, M.F.: Industry 4.0: a review on industrial automation and robotic. J. Teknol. 78(6–13), 137–143 (2016)

[3]

Pfeiffer, S.: Robots, industry 4.0 and humans, or why assembly work is more than routine work. Societies 6(2), 16 (2016)

[4]

Shyvakov, O.: Developing a security framework for robots. Master’s thesis, University of Twente (2017)

[5]

Simoens P, Dragone M, and Saffiotti A The internet of robotic things: a review of concept, added value and applications Int. J. Adv. Robot. Syst. 2018 15 1 1729881418759424

[6]

Chui M, Manyika J, and Miremadi M Where machines could replace humans-and where they can’t (yet) McKinsey Q. 2016 7 1-6

[7]

Kirschgens, L.A., Ugarte, I.Z., Uriarte, E.G., Rosas, A.M., Vilches, V.M.: Robot hazards: from safety to security (2018). arXiv preprint arXiv:1806.06681

[8]

Guerrero-Higueras ÁM, DeCastro-Garcia N, and Matellan V Detection of cyber-attacks to indoor real time localization systems for autonomous robots Robot. Auton. Syst. 2018 99 75-83

[9]

Petit J and Shladover SE Potential cyberattacks on automated vehicles IEEE Trans. Intell. Transp. Syst. 2015 16 2 546-556

[10]

Cerrudo C and Apa L Hacking robots before skynet 2017 IOActive Report, Seattle, USA Cybersecurity Insight

[11]

Vuong, T., Filippoupolitis, A., Loukas, G., Gan, D.: Physical indicators of cyber attacks against a rescue robot. In: 2014 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 338–343. IEEE (2014)

[12]

Dash P, Karimibiuki M, and Pattabiraman K Stealthy attacks against robotic vehicles protected by control-based intrusion detection techniques J. Digit. Threats Res. Pract. 2021 2 1 1-25

[13]

Chowdhury, A., Karmakar, G., Kamruzzaman, J.: Survey of recent cyber security attacks on robotic systems and their mitigation approaches. In: Cyber Law, Privacy, and Security: Concepts, Methodologies, Tools, and Applications, pp. 1426–1441. IGI Global (2019)

[14]

Lacava, G., Marotta, A., Martinelli, F., Saracino, A., La Marra, A., Gil-Uriarte, E., Vilches, V.M.: Current research issues on cyber security in robotics (2020)

[15]

Mitchell R and Chen I-R A survey of intrusion detection techniques for cyber-physical systems ACM Comput. Surv. (CSUR) 2014 46 4 55

[16]

Kehoe B, Patil S, Abbeel P, and Goldberg K A survey of research on cloud robotics and automation IEEE Trans. Autom. Sci. Eng. 2015 12 2 398-409

[17]

Chowdhury, A., Karmakar, G., Kamruzzaman, J.: Survey of recent cyber security attacks on robotic systems and their mitigation approaches. In: Detecting and Mitigating Robotic Cyber Security Risks, pp. 284–299. IGI Global (2017)

[18]

Jeong, S.-Y., Choi, I.-J., Kim, Y.-J., Shin, Y.-M., Han, J.-H., Jung, G.-H., Kim, K.-G.: A study on ros vulnerabilities and countermeasure. In: Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human–Robot Interaction, pp. 147–148. ACM (2017)

[19]

Hellaoui H, Koudil M, and Bouabdallah A Energy-efficient mechanisms in security of the internet of things: a survey Comput. Netw. 2017 127 173-189

[20]

Guiochet J, Machin M, and Waeselynck H Safety-critical advanced robots: a survey Robot. Auton. Syst. 2017 94 43-52

[21]

Dieber B, Breiling B, Taurer S, Kacianka S, Rass S, and Schartner P Security for the robot operating system Robot. Auton. Syst. 2017 98 192-203

[22]

Alcaraz, C., Cazorla, L., Lopez, J.: Cyber-physical systems for wide-area situational awareness. In: Cyber-Physical Systems, pp. 305–317. Elsevier (2017)

[23]

Rubio JE, Alcaraz C, Roman R, and Lopez J Current cyber-defense trends in industrial control systems Comput. Secur. 2019 87 101561

[24]

Jahan F, Sun W, Niyaz Q, and Alam M Security modeling of autonomous systems: a survey ACM Comput. Surv. (CSUR) 2019 52 5 1-34

[25]

Chen, J., Li, K., Zhang, Z., Li, K., Yu, P.S.: A survey on applications of artificial intelligence in fighting against covid-19 (2020). arXiv preprint arXiv:2007.02202

[26]

Brem A, Viardot E, and Nylund PA Implications of the coronavirus (covid-19) outbreak for innovation: which technologies will improve our lives? Technol. Forecast. Soc. Change 2020 163

[27]

Khan, F.N., Khanam, A.A., Ramlal, A., Ahmad, S.: A review on predictive systems and data models for covid-19. In: Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis, pp. 123–164. Springer (2020)

[28]

Fan D, Li Y, Liu W, Yue X-G, and Boustras G Weaving public health and safety nets to respond the covid-19 pandemic Saf. Sci. 2020 134 105058

[29]

Bokolo Anthony Jnr Use of telemedicine and virtual care for remote treatment in response to covid-19 pandemic J. Med. Syst. 2020 44 7 1-9

[30]

Yaacoub J-PA, Noura HN, Salman O, and Chehab A Security analysis of drones systems: attacks, limitations, and recommendations Internet Things 2020 11 100218

[31]

Wang, H., Cheng, H., Hao, H.: The use of unmanned aerial vehicle in military operations. In: International Conference on Man–Machine–Environment System Engineering, pp. 939–945. Springer (2020)

[32]

Kamel MA, Yu X, and Zhang Y Formation control and coordination of multiple unmanned ground vehicles in normal and faulty situations: a review Annu. Rev. Control 2020 49 128-144

[33]

Nandyal, A.A., Adithya, D.M., Karthik, K., Manikantan, G., Sudha, P.N.: A literature survey on “unmanned underwater vehicle for monitoring aquatic ecosystem”. Int. J. Eng. Appl. Sci. Technol. 5(2), 599–601 (2020). (ISSN: 2455-2143)

[34]

He, Y., Wang, D.B., Ali, Z.A.: A review of different designs and control models of remotely operated underwater vehicle. Meas. Control, p. 0020294020952483 (2020)

[35]

Yaacoub J-PA, Salman O, Noura HN, Kaaniche N, Chehab A, and Malli M Cyber-physical systems security: limitations, issues and future trends Microprocess. Microsyst. 2020 77 102019

[36]

Yaacoub JPA, Fernandez JH, Noura HN, and Chehab A Security of power line communication systems: issues, limitations and existing solutions Comput. Sci. Rev. 2021 39 100331

[37]

Yaacoub J-PA, Noura M, Noura HN, Salman O, Yaacoub E, Couturier R, and Chehab A Securing internet of medical things systems: limitations, issues and recommendations Future Gener. Comput. Syst. 2020 105 581-606

[38]

Gogu, G., Ray, P., Neagoe, M., Gogu, G., Diaconescu, D., Pocola, A.G., Pop, D.O., Petra, C.: Robotics and manufacturing. In: Talaba, D., Roche, T. (eds.) Product Engineering: Eco-Design, Technologies and Green Energy, p. 348. Springer, Cham (2006)

[39]

Kadir MA Role of telemedicine in healthcare during covid-19 pandemic in developing countries 2020 Today Telehealth Med

[40]

Beasley, R.A.: Medical robots: current systems and research directions. J. Robot. (2012)

[41]

Rosen J and Hannaford B Doc at a distance IEEE Spectr. 2006 43 10 34-39

[42]

Cheein FAA and Carelli R Agricultural robotics: unmanned robotic service units in agricultural tasks IEEE Ind. Electron. Mag. 2013 7 3 48-58

[43]

Murphy RR, Tadokoro S, Nardi D, Jacoff A, Fiorini P, Choset H, and Erkmen AM Siciliano B and Khatib O Search and rescue robotics Springer Handbook of Robotics 2008 Berlin Springer 1151-1173

[44]

Murphy RR, Tadokoro S, and Kleiner A Siciliano B and Khatib O Disaster robotics Springer Handbook of Robotics 2016 Berlin Springer 1577-1604

[45]

Stager, P.: Visual search capability in search and rescue(sar) (1974)

[46]

McKirdy, E.: Thailand cave rescue: boys appear in new video, ‘i am healthy’ (2018)

[47]

Naghsh, A.M., Gancet, J., Tanoto, A., Roast, C.: Analysis and design of human–robot swarm interaction in firefighting. In: The 17th IEEE International Symposium on Robot and Human Interactive Communication, 2008. RO-MAN 2008, pp. 255–260. IEEE (2008)

[48]

Hong, J.H., Matson, E.T., Taylor, J.M.: Design of knowledge-based communication between human and robot using ontological semantic technology in firefighting domain. In: Robot Intelligence Technology and Applications, vol. 2, pp. 311–325. Springer (2014)

[49]

Mansour, H., Bitar, E., Fares, Y., Makdessi, A., Maalouf, A., El Ghoul, M., Mansour, M., Chami, A., Khalil, M., Jalkh, A., et al.: Beirut port ammonium nitrate explosion. SSRN (2020)

[50]

Cheaito MA and Al-Hajj S A brief report on the beirut port explosion 2020 Acute Care Mediterr. J. Emerg. Med

[51]

Oxford Analytica. Beirut blast could bring hunger, disease and fury. Emerald Expert Briefings (2020)

[52]

Stennett C, Gaulter S, and Akhavan J An estimate of the TNT-equivalent net explosive quantity (NEQ) of the Beirut port explosion using publicly-available tools and data Propellants Explos, Pyrotech. 2020 45 11 1675-1679

[53]

Thielman, S.: Use of police robot to kill Dallas shooting suspect believed to be first in US history. The Guardian (2016)

[54]

Ringrose K and Ramjee D Watch where you walk: law enforcement surveillance and protester privacy Calif. L. Rev. Online 2020 11 349

[55]

Schulte, P.: Future war: Ai, drones, terrorism and counterterror. In: Handbook of Terrorism and Counter Terrorism Post 9/11. Edward Elgar Publishing (2019)

[56]

Zych J The use of weaponized kites and balloons in the Israeli-Palestinian conflict Secur. Def. Q. 2019 27 5 71-83

[57]

Engberts, B., Gillissen, E.: Policing from above: drone use by the police. In: The Future of Drone Use, pp. 93–113. Springer (2016)

[58]

Shachtman, N.: Military stats reveal epicenter of us drone war. Wired. com 9 (2012)

[59]

Wilson, C.: Improvised explosive devices in Iraq: effects and countermeasures. In: CRS Report for Congress, Library of Congress Washington DC Congressional Research Service (2005)

[60]

Lesley-Dixon, K.: Northern Ireland: the troubles: from the provos to the det, 1968–1998. Pen and Sword (2018)

[61]

Miller D Rethinking Northern Ireland: Culture 2014 London Ideology and Colonialism. Routledge

[62]

Krishnan A Killer Robots: Legality and Ethicality of Autonomous Weapons 2016 London Routledge

[63]

Barboza, A.R.: The Irish Republican Army: an examination of imperialism, terror, and just war theory. Master’s thesis, California Polytechnic State University, San Luis Obispo (2020)

[64]

Karnozov V et al. Russia and Turkey put their latest equipment to the test in Syria Def. Rev. Asia 2020 14 2 20

[65]

Zoltán Ő Special features of the Russian-Ukrainian armed conflict Hadmérnök 2020 15 1 207-220

[66]

Okpaleke, F., Burton, J.: 9 US grand strategy and the use of unmanned aerial vehicles during the George W. Bush administration. In: Emerging Technologies and International Security: Machines, the State, and War, p. 153 (2020)

[67]

Scipanov LV and Dolceanu D The opportunity for using remotely operated underwater vehicles in support of naval actions Bull. Carol I Natl. Def. Univ. 2020 9 3 62-68

[68]

Siwek, M., Wacławik, K.: Legal aspects of production and operation of autonomous combat robots. Problemy Mechatroniki: uzbrojenie, lotnictwo, inżynieria bezpieczeństwa, 11 (2020)

[69]

Thornton R and Miron M Towards the ‘third revolution in military affairs’ the Russian military’s use of AI-enabled cyber warfare RUSI J. 2020 165 1-10

[70]

Abiodun, T.F., Taofeek, C.R.: Unending war on boko haram terror in northeast Nigeria and the need for deployment of military robots or autonomous weapons systems to complement military operations. Journal DOI 6(6) (2020)

[71]

Westerheijden, V.R.: Remote warfare comes home: an inquiry in the Dutch government’s development of discourse on airstrikes and drones between 1998–2020. Master’s thesis, Utrecht University (2020)

[72]

Oxford Analytica: Uae’s bolstering of Libya’s haftar is a risky policy. Emerald Expert Briefings (oxan-db) (2020)

[73]

Milan FF and Tabrizi AB Armed, unmanned, and in high demand: the drivers behind combat drones proliferation in the Middle East Small Wars Insurgencies 2020 31 4 730-750

[74]

Gallagher, K.: Killer optics: exports of Wescam sensors to Turkey (2020)

[75]

Clark, M., Yazici, E.: Erdogan seeks to upend kremlin-backed status quo in Nagorno-Karabakh. Institute for the Study of War, p. 1 (2020)

[76]

Tol, T., et al.: Transitions online\_around the bloc-Tuesday, 27 October 2020. Transitions Online (11/02):9–11 (2020)

[77]

Khan, N., Fahad, S., Naushad, M., Faisal, S.: Analysis of Arminia and Azerbijan war and its impact on both countries economies. Available at SSRN 3709329 (2020)

[78]

Jenzen-Jones, N.R.: Understanding the threat posed by cots small UAVs armed with CBR payloads. In: 21st Century Prometheus, pp. 179–204. Springer (2020)

[79]

Kaya, E.K.: Walking a fragile path: assessing the idlib de-militarization deal (2018)

[80]

Sadat, S.A.: Iran ties to the Palestinian Islamic resistance movement with emphasis on the Islamic Jihad Movement (PIJ), pp. 77–105 (2016)

[81]

Bendett, S.: Battle robots rivalry and the future of war (2019)

[82]

Brookes, P.: The growing Iranian unmanned combat aerial vehicle threat needs us action. Herit. Found. Backgr. 3437 (2019)

[83]

Sims A The rising drone threat from terrorists Georget. J. Int. Aff. 2018 19 97-107

[84]

Rossiter A Bots on the ground: an impending UGV revolution in military affairs? Small Wars Insurgencies 2020 31 4 851-873

[85]

Chávez K and Swed O Off the shelf: the violent nonstate actor drone threat Air Space Power J. 2020 29 29

[86]

Vogiatzis, D.: The way to the promised land or the door to Armageddon: how severe are the threats against the physical security of israeli offshore gas platforms? Naval Postgraduate School, Monterey, CA. Ph.D. thesis (2020)

[87]

Borg, S.: Assembling Israeli drone warfare: loitering surveillance and operational sustainability. Security Dialogue, p. 0967010620956796 (2020)

[88]

Benjamin, G.: Drone culture: perspectives on autonomy and anonymity. AI & SOCIETY, pp. 1–11 (2020)

[89]

Popister, F., Steopan, M., Pusca, A.: Surveillance robot for military use. Acta Tech. Napocensis-Ser. Appl. Math. Mech. Eng. 63(3) (2020)

[90]

Fishman J and Kuperwasser Y Willful blindness and the mistake of underestimation: the Oslo gamble Natl. Resili. Polit. Soc. 2020 2 1 9-50

[91]

Marcus RD Learning ‘under fire’: Israel’s improvised military adaptation to Hamas tunnel warfare J. Strateg. Stud. 2019 42 3–4 344-370

[92]

Michael, K., Dostri, O.: The Hamas military buildup. The crisis of the Gaza strip: a way out (Tel Aviv: INSS, 2017), pp. 49–60 (2019)

[93]

White J The combat performance of Hamas in the Gaza war of 2014 CTC Sentin 2014 7 9 9-13

[94]

Gillespie PG Weapons of choice: the development of precision guided munitions 2006 Tuscaloosa The University of Alabama Press

[95]

Fink, A.H., Wilson, W.A., Holte, R.T.: System and methods for countering satellite-navigated munitions, December 20 2016. US Patent 9,523,773

[96]

Ahner D and McCarthy A Response surface modeling of precision-guided fragmentation munitions J. Def. Model. Simul. 2020 17 1 83-97

[97]

O’Donohue, Commander Mark: Autonomous underwater vehicles. Niobe Papers 9(11) (2020)

[98]

Keane J and Joiner K Experimental test and evaluation of autonomous underwater vehicles Aust. J. Multi-Discip. Eng. 2020 16 1 67-79

[99]

Nasu H and Letts D The legal characterization of lethal autonomous maritime systems: warship, torpedo, or naval mine? Int. Law Stud. 2020 96 1 4

[100]

Mvelle G Fighting piracy in the gulf of guinea: small states’ pursuit of strategic autonomy Revue internationale et strategique 2020 2 35-46

[101]

Broohm DA, Wang G, and Gao J Maritime security: a new strategy for merchant shipping to avoid piracy in the Gulf of Guinea Open J. Soc. Sci. 2020 8 5 392-410

[102]

Grasso, R., Braca, P., Osler, J., Hansen, J.: Asset network planning: integration of environmental data and sensor performance for counter piracy. In: 21st European Signal Processing Conference (EUSIPCO 2013), pp. 1–5. IEEE (2013)

[103]

Karahalios H Appraisal of a ship’s cybersecurity efficiency: the case of piracy J. Transp. Secur. 2020 13 1-23

[104]

AU African Union, COIN Counterinsurgency, and CT Counterterrorism. Ctf counter terrorist financing ctf 150 combined task force 150 cwc chemical weapons convention dfg deutsche forschungsgemeinschaft/German research foundation

[105]

Beccaro A Isis in mosul and sirte: differences and similarities Mediterr. Polit. 2018 23 3 410-417

[106]

Bunker RJ Keshavarz 2016 Alma Terrorist and insurgent teleoperated sniper rifles and machine guns

[107]

Beccaro, A.: Isis in Libya and beyond, 2014–2016. J. N. Afr. Stud. 1–20 (2020)

[108]

Gibbons-Neff, T.: Isis drones are attacking us troops and disrupting airstrikes in Raqqa, officials say. Washington Post 14 (2017)

[109]

Hoenig, M.: Hezbollah and the use of drones as a weapon of terrorism. Public Interest Rep. 67(2) (2014)

[110]

Stalinsky, S., Sosnow, R.: A decade of jihadi organizations’ use of drones—from early experiments by Hizbullah, Hamas, and Al-Qaeda to emerging national security crisis for the west as ISIS launches first attack drones. MEMRI-The Middle East Media Research Institute. February, 21 (2017)

[111]

Shay, S.: The Houthi Maritime Threats in the Red Sea Basin, vol. 9. Institute for Policy and Strategy (2017)

[112]

Rossiter A Drone usage by militant groups: exploring variation in adoption Def. Secur. Anal. 2018 34 2 113-126

[113]

Sana’a Center. Drone wars (2019)

[114]

Archambault E and Veilleux-Lepage Y Drone imagery in Islamic state propaganda: flying like a state Int. Aff. 2020 96 4 955-973

[115]

Naudé, W.: Artificial intelligence vs covid-19: limitations, constraints and pitfalls. Ai & Society, p. 1 (2020)

[116]

Moon MJ Fighting COVID-19 with agility, transparency, and participation: Wicked policy problems and new governance challenges Public Adm. Rev. 2020 80 4 651-656

[117]

Yakas, B.: Faa investigating” anti-covid-19 volunteer drone” filmed admonishing people in nyc (2020)

[118]

Scott, J.E., Scott, C.H.: Models for drone delivery of medications and other healthcare items. In: Unmanned Aerial Vehicles: Breakthroughs in Research and Practice, pp. 376–392. IGI Global (2019)

[119]

Ye J The role of health technology and informatics in a global public health emergency: practices and implications from the covid-19 pandemic JMIR Med. Inform. 2020 8 7, e19866

[120]

Abubakar, A.I., Omeke, K.G.,Öztürk, M., Hussain, S. and Imran, M.A.: The role of artificial intelligence driven 5G networks in COVID-19 outbreak: opportunities, challenges, and future outlook. Front. Comms. Net. (2020)

[121]

Nair VV Drones as futuristic crime prevention strategy: situational review during covid-19 lockdown J. Soc. Sci. 2020 64 1–3 22-29

[122]

Jat, D.S., Singh, C.: Artificial intelligence-enabled robotic drones for covid-19 outbreak. In: Intelligent Systems and Methods to Combat Covid-19, pp. 37–46. Springer (2020)

[123]

Oguamanam, C.: Covid-19 and Africa: does one size fit all in public health intervention? Vulnerable: The Policy, Law and Ethics of COVID-19.University of Ottawa Press, Ottawa (2020) (Forthcoming in 2020)

[124]

Vafea MT, Atalla E, Georgakas J, Shehadeh F, Mylona EK, Kalligeros M, and Mylonakis E Emerging technologies for use in the study, diagnosis, and treatment of patients with covid-19 Cell. Mol. Bioeng. 2020 13 4 249-257

[125]

Zeng Z, Chen P-J, and Lew AA From high-touch to high-tech: Covid-19 drives robotics adoption Tour. Geogr. 2020 22 1-11

[126]

Bhaskar S, Bradley S, Sakhamuri S, Moguilner S, Chattu VK, Pandya S, Schroeder S, Ray D, and Banach M Designing futuristic telemedicine using artificial intelligence and robotics in the covid-19 era Front. Public Health 2020 8 708

[127]

Odekerken-Schröder, G., Mele, C., Russo-Spena, T., Mahr, D., Ruggiero, A.: Mitigating loneliness with companion robots in the covid-19 pandemic and beyond: an integrative framework and research agenda. J. Serv. Manag. (2020)

[128]

Bhardwaj A, Avasthi V, and Goundar S Cyber security attacks on robotic platforms Netw. Secur. 2019 2019 10 13-19

[129]

Wang, C., Carzaniga, A., Evans, D., Wolf, A.: Security issues and requirements for internet-scale publish-subscribe systems. In: HICSS, p. 303. IEEE (2002)

[130]

Esposito C and Ciampi M On security in publish/subscribe services: a survey IEEE Commun. Surv. Tutor. 2015 17 2 966-997

[131]

Dzung D, Naedele M, Von Hoff TP, and Crevatin M Security for industrial communication systems Proc. IEEE 2005 93 6 1152-1177

[132]

Laitinen A, Niemelä M, and Pirhonen J Demands of dignity in robotic care: recognizing vulnerability, agency, and subjectivity in robot-based, robot-assisted, and teleoperated elderly care Tech. Res. Philos. Technol. 2019 23 3 366-401

[133]

Choi, H., Kate, S., Aafer, Y., Zhang, X., Xu, D.: Cyber-physical inconsistency vulnerability identification for safety checks in robotic vehicles. In: Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security, pp. 263–278 (2020)

[134]

Atamli, A.W., Martin, A.: Threat-based security analysis for the internet of things. In: 2014 International Workshop on Secure Internet of Things (SIoT), pp. 35–43. IEEE (2014)

[135]

Hou, T., Wang, V.: Industrial espionage-a systematic literature review (slr). Comput. Secur. 98, 102019 (2020)

[136]

Siman-Tov, D., Even, S.: A new level in the cyber war between Israel and Iran. INSS Insight (1328) (2020)

[137]

Losa, L.: The impact of cyber capabilities on the Israeli–Iranian relationship (2020)

[138]

Kaye DD and Efron S Israel’s evolving Iran policy Survival 2020 62 4 7-30

[139]

Yousef KMA, AlMajali A, Ghalyon SA, Dweik W, and Mohd BJ Analyzing cyber-physical threats on robotic platforms Sensors 2018 18 5 1643

[140]

Eun Y-S and Aßmann JS Cyberwar: taking stock of security and warfare in the digital age Int. Stud. Perspect. 2016 17 3 343-360

[141]

Geerts, M.: Digitalization combined with organizational process innovation. The solution to the risk of industrial espionage? (2020)

[142]

Klebanov LR and Polubinskaya SV Computer technologies for committing sabotage and terrorism RUDN J. Law 2020 24 3 717-734

[143]

Astor, M.: Your roomba may be mapping your home, collecting data that could be shared—the New York times. https://www.nytimes.com/2017/07/25/technology/roomba-irobot-data-privacy.html (2017)

[144]

Sollins, K.R.: Iot big data security and privacy vs. innovation. IEEE Internet Things J. 6, 1–1 (2019)

[145]

Noura, H.N., Hatoum, T., Salman, O., Yaacoub, J.-P., Chehab, A.: Lorawan security survey: issues, threats and possible mitigation techniques. Internet of Things, p. 100303 (2020)

[146]

Salamai A, Hussain OK, Saberi M, Chang E, and Hussain FK Highlighting the importance of considering the impacts of both external and internal risk factors on operational parameters to improve supply chain risk management IEEE Access 2019 7 49297-49315

[147]

Priyadarshini, I.: Cyber security risks in robotics. In: Cyber Security and Threats: Concepts, Methodologies, Tools, and Applications, pp. 1235–1250. IGI Global (2018)

[148]

Sobb T, Turnbull B, and Moustafa N Supply chain 4.0: a survey of cyber security challenges, solutions and future directions Electronics 2020 9 11 1864

[149]

Sha K, Yang TA, Wei W, and Davari S A survey of edge computing-based designs for IoT security Digit. Commun. Netw. 2020 6 2 195-202

[150]

Gaikwad NB, Ugale H, Keskar A, and Shivaprakash NC The internet of battlefield things (IoBT) based enemy localization using soldiers location and gunshot direction IEEE Internet of Things J. 2020 7 12 11725-11734

[151]

Tehranipoor, M., Koushanfar, F.: A survey of hardware Trojan taxonomy and detection. IEEE Des. Test Comput. 27(1), 10–25 (2010)

[152]

Wang, X., Mal-Sarkar, T., Krishna, A., Narasimhan, S., Bhunia, S.: Software exploitable hardware Trojans in embedded processor. In: 2012 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT), pp. 55–58. IEEE (2012)

[153]

Elmiligi H, Gebali F, and El-Kharashi MW Multi-dimensional analysis of embedded systems security Microprocess. Microsyst. 2016 41 29-36

[154]

Clark, G.W., Doran, M.V., Andel, T.R.: Cybersecurity issues in robotics. In: 2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA), pp. 1–5. IEEE (2017)

[155]

Falliere, N., Murchu, L.O., Chien, E.: W32. stuxnet dossier. White paper, Symantec Corp., Security Response 5(6), 29 (2011)

[156]

Goyal R, Sharma S, Bevinakoppa S, and Watters P Obfuscation of stuxnet and flame malware Latest Trends Appl. Inform. Comput. 2012 150 154

[157]

Bencsáth B, Pék G, Buttyán L, and Felegyhazi M The cousins of stuxnet: Duqu, flame, and gauss Future Internet 2012 4 4 971-1003

[158]

Kamiński MA Operation “olympic games.” Cyber-sabotage as a tool of American intelligence aimed at counteracting the development of Iran’s nuclear programme Secur. Def. Q. 2020 29 2 63-71

[159]

Horschig D Cyber-weapons in nuclear counter-proliferation Def. Secur. Anal. 2020 36 3 352-371

[160]

Fruhlinger, J.: What is wannacry ransomware, how does it infect, and who was responsible (2017)

[161]

Stallings W Cryptography and Network Security: Principles and Practice 2017 Upper Saddle River Pearson

[162]

Monikandan S and Arockiam L Confidentiality technique to enhance security of data in public cloud storage using data obfuscation Indian J. Sci. Technol. 2015 8 24 1

[163]

Bellovin, S.M., Merritt, M.: Encrypted key exchange: password-based protocols secure against dictionary attacks. In: 1992 IEEE Computer Society Symposium on Research in Security and Privacy, 1992. Proceedings, pp. 72–84. IEEE (1992)

[164]

Irani, D., Balduzzi, M., Balzarotti, D., Kirda, E., Pu, C.: Reverse social engineering attacks in online social networks. In: International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, pp. 55–74. Springer (2011)

[165]

Khan, M.H., Shah, M.A.: Survey on security threats of smartphones in internet of things. In: 2016 22nd International Conference on Automation and Computing (ICAC), pp. 560–566. IEEE (2016)

[166]

Kc, G.S., Keromytis, A.D., Prevelakis, V.: Countering code-injection attacks with instruction-set randomization. In: Proceedings of the 10th ACM Conference on Computer and Communications Security, pp. 272–280. ACM (2003)

[167]

Miller, J., Williams, A.B., Perouli, D.: A case study on the cybersecurity of social robots. In: Companion of the 2018 ACM/IEEE International Conference on Human–Robot Interaction, pp. 195–196. ACM (2018)

[168]

Shahbaznezhad, H., Kolini, F., Rashidirad, M.: Employees’ behavior in phishing attacks: what individual, organizational, and technological factors matter? J. Comput. Inf. Syst. 1–12 (2020)

[169]

Alabdan R Phishing attacks survey: types, vectors, and technical approaches Future Internet 2020 12 10 168

[170]

Mo, Y., Garone, E., Casavola, A., Sinopoli, B.: False data injection attacks against state estimation in wireless sensor networks. In: 2010 49th IEEE Conference on Decision and Control (CDC), pp. 5967–5972. IEEE (2010)

[171]

Senie, D., Ferguson, P.: Network ingress filtering: defeating denial of service attacks which employ IP source address spoofing. Network (1998)

[172]

Gu, Q.: Packet-dropping attack. In: Encyclopedia of Cryptography and Security, pp. 899–902. Springer (2011)

[173]

Navas, R.E., Le Bouder, H., Cuppens, N., Cuppens, F., Papadopoulos, G.Z.: Do not trust your neighbors! a small IoT platform illustrating a man-in-the-middle attack. In: International Conference on Ad-Hoc Networks and Wireless, pp. 120–125. Springer (2018)

[174]

Chen, X., Liu, C., Li, B., Lu, K., Song, D.: Targeted backdoor attacks on deep learning systems using data poisoning (2017). arXiv preprint arXiv:1712.05526

[175]

Alemzadeh, H., Chen, D., Li, X., Kesavadas, T., Kalbarczyk, Z.T., Iyer, R.K.: Targeted attacks on teleoperated surgical robots: dynamic model-based detection and mitigation. In: 2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 395–406. IEEE (2016)

[176]

Halderman JA, Schoen SD, Heninger N, Clarkson W, Paul W, Calandrino JA, Feldman AJ, Appelbaum J, and Felten EW Lest we remember: cold-boot attacks on encryption keys Commun. ACM 2009 52 5 91-98

[177]

Blackwell, T., Casner, D., Nelson, B., Wiley, S.: Self-balancing robot including an ultracapacitor power source, October 18 2011. US Patent 8,041,456

[178]

Abomhara M and Køien GM Cyber security and the internet of things: vulnerabilities, threats, intruders and attacks J. Cyber Secur. 2015 4 1 65-88

[179]

Rajendran J, Kanuparthi AK, Zahran M, Addepalli SK, Ormazabal G, and Karri R Securing processors against insider attacks: a circuit-microarchitecture co-design approach IEEE Des. Test 2013 30 2 35-44

[180]

Larson, S.: Ransomware experiment shows the dangers of hacking robots. https://money.cnn.com/2018/03/09/technology/robots-ransomware/index.html (2018)

[181]

Mansor, H., Markantonakis, K., Akram, R.N., Mayes, K.: Don’t brick your car: firmware confidentiality and rollback for vehicles. In: 2015 10th International Conference on Availability, Reliability and Security (ARES), pp. 139–148. IEEE (2015)

[182]

Feily, M., Shahrestani, A., Ramadass, S.: A survey of botnet and botnet detection. In: Third International Conference on Emerging Security Information, Systems and Technologies, 2009. SECURWARE’09, pp. 268–273. IEEE (2009)

[183]

Yih-Chun H, Perrig A, and Johnson DB Wormhole attacks in wireless networks IEEE J. Sel. Areas Commun. 2006 24 2 370-380

[184]

Baccelli, E., Hahm, O., Gunes, M., Wahlisch, M., Schmidt, T.C.: Riot os: Towards an os for the internet of things. In: 2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 79–80. IEEE (2013)

[185]

Azar, C., Brostoff, G.: System and method for providing secure access to an electronic device using continuous facial biometrics, February 5 2013. US Patent 8,370,639

[186]

Azar, C., Brostoff, G.: System and method for providing secure access to an electronic device using both a screen gesture and facial biometrics, January 7 2014. US Patent 8,627,096

[187]

Tasevski P Password Attacks and Generation Strategies 2011 Tartu Tartu University, Faculty of Mathematics and Computer Sciences

[188]

Hoelscher, P.: Phishing networks. https://resources.infosecinstitute.com/category/enterprise/phishing/phishing-attack-overview/phishing-networks/#gref

[189]

Neumann PG Denial-of-service attacks Commun. ACM 2000 43 4 136-136

[190]

Side-Channel Attacks. Side-channel attacks

[191]

Amoozadeh M, Raghuramu A, Chuah C-N, Ghosal D, Zhang HM, Rowe J, and Levitt K Security vulnerabilities of connected vehicle streams and their impact on cooperative driving IEEE Commun. Mag. 2015 53 6 126-132

[192]

Chesaux, J.: Wireless access point spoofing and mobile devices geolocation using swarms of flying robots. Master optional semester project, Spring (2014)

[193]

Kaufman, C.W., Pearlman, R.J., Gasser, M.: System for increasing the difficulty of password guessing attacks in a distributed authentication scheme employing authentication tokens, February 13 1996. US Patent 5,491,752

[194]

Barcena, M.B., Wueest, C.: Insecurity in the internet of things. Security Response, Symantec (2015)

[195]

Kumar R, Pattnaik PK, and Pandey P Detecting and Mitigating Robotic Cyber Security Risks 2017 Hershey IGI Global

[196]

Schultz EE and Ray E Rootkits: the ultimate malware threat Inf. Secur. Manag. Handb. 2008 2 175

[197]

Denning, T., Matuszek, C., Koscher, K., Smith, J.R., Kohno, T.: A spotlight on security and privacy risks with future household robots: attacks and lessons. In: Proceedings of the 11th International Conference on Ubiquitous Computing, pp. 105–114. ACM (2009)

[198]

Jiang, D., Omote, K.: An approach to detect remote access trojan in the early stage of communication. In: 2015 IEEE 29th International Conference on Advanced Information Networking and Applications (AINA), pp. 706–713. IEEE (2015)

[199]

Maglaras, L.A., Jiang, J.: Intrusion detection in Scada systems using machine learning techniques. In: Science and Information Conference (SAI), 2014, pp. 626–631. IEEE (2014)

[200]

Block J A laws of war review of contemporary land-based missile defence system ‘iron dome’ Sci. Mil. S. Afr. J. Mil. Stud. 2017 45 2 105-128

[201]

Schneider P and IFSH Hamburg Recent trends in global maritime terrorism Marit. Secur. Count. Terror. Lessons Marit. Piracy Narc. Interdiction 2020 150 187

[202]

Patterson, D.A., Bridgelall, R.: Attack risk modelling for the San Diego maritime facilities. Mar. Policy 104210 (2020)

[203]

Morris, I.: War! what is it good for?: conflict and the progress of civilization from primates to robots. Farrar, Straus and Giroux (2014)

[204]

Button, M.: Economic and industrial espionage (2020)

[205]

Oruc, A., Sc MIET MIMarEST, M.: Claims of state-sponsored cyberattack in the maritime industry

[206]

Cellan-Jones, R.: Robots ‘to replace up to 20 million factory jobs’ by 2030. https://www.bbc.com/news/business-48760799 (27.01. 2020) (2019)

[207]

Vermeulen, B., Pyka, A., Saviotti, P.P.: A taxonomic structural change perspective on the economic impact of robots and artificial intelligence on creative work. In: The Future of Creative Work. Edward Elgar Publishing (2020)

[208]

Cooper, A.: How robots change the world; what automation really means for jobs and productivity. Technical report (Tech. Rep.). Oxford Economics, Oxford (2019)

[209]

Acemoglu D and Restrepo P Robots and jobs: evidence from US labor markets J. Polit. Econ. 2020 128 6 2188-2244

[210]

Alemzadeh H, Raman J, Leveson N, Kalbarczyk Z, and Iyer RK Adverse events in robotic surgery: a retrospective study of 14 years of FDA data PloS one 2016 11 4 e0151470

[211]

Bloomfield, R.E.G.: Bullets to bytes: defending the United Kingdom in cyberspace (2019)

[212]

Rotjan RD, Blum J, and Lewis SM Shell choice in pagurus longicarpus hermit crabs: does predation threat influence shell selection behavior? Behav. Ecol. Sociobiol. 2004 56 2 171-176

[213]

Peterson, A.: Yes, terrorists could have hacked Dick Cheney’s heart. Washington Post (2013)

[214]

Senthilkumar, K.S., Pirapaharan, K., Julai, N., Hoole, P.R.P., Othman, A.-H., Harikrishnan, R., Hoole, S.R.H.: Perceptron ANN control of array sensors and transmitters with different activation functions for 5g wireless systems. In: 2017 International Conference on Signal Processing and Communication (ICSPC), pp. 107–111. IEEE (2017)

[215]

Checkoway, S., McCoy, D., Kantor, B., Anderson, D., Shacham, H., Savage, S., Koscher, K., Czeskis, A., Roesner, F., Kohno, T., et al.: Comprehensive experimental analyses of automotive attack surfaces. In: USENIX Security Symposium, pp. 77–92. San Francisco (2011)

[216]

Turner A, Glantz K, and Gall J A practitioner-researcher partnership to develop and deliver operational value of threat, risk and vulnerability assessment training to meet the requirements of emergency responders J. Homel. Secur. Emerg. Manag. 2013 10 1 319-332

[217]

Moalla, R., Labiod, H., Lonc, B., Simoni, N.: Risk analysis study of its communication architecture. In: 2012 Third International Conference on the Network of the Future (NOF), pp. 1–5. IEEE (2012)

[218]

Alberts, C.J., Behrens, S.G., Pethia, R.D., Wilson, W.R.: Operationally critical threat, asset, and vulnerability evaluation (octave) framework, version 1.0. Technical report, Carnegie-Mellon Univ Pittsburgh PA Software Engineering Inst (1999)

[219]

Zahra, B.F., Abdelhamid, B.: Risk analysis in internet of things using EBIOS. In: 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), pp. 1–7. IEEE (2017)

[220]

Méthode Harmonisée d’Analyse de Risques. Mehari. CLUSIF, France (2007)

[221]

Barber B and Davey J The use of the CCTA risk analysis and management methodology Cramm in health information systems Medinfo 1992 92 1589-1593

[222]

Secrétariat Général Défense Nationale. Ebios-expression des besoins et identification des objectifs de sécurité (2004)

[223]

Süzen, A.A.: A risk-assessment of cyber attacks and defense strategies in industry 4.0 ecosystem. Int. J. Comput. Netw. Inf. Secur. 12(1) (2020)

[224]

Brandstötter, M., Komenda, T., Ranz, F., Wedenig, P., Gattringer, H., Kaiser, L., Breitenhuber, G., Schlotzhauer, A., Müller, A., Hofbaur, M.: Versatile collaborative robot applications through safety-rated modification limits. In: International Conference on Robotics in Alpe-Adria Danube Region, pp. 438–446. Springer (2019)

[225]

Komenda, T., Steiner, M., Rathmair, M., Brandstötter, M.: Introducing a morphological box for an extended risk assessment of human-robot work systems considering prospective system modifications. Gra, In: Joint Austrian Computer Vision and Robotics WorkshopAt (2019)

[226]

Chemweno P, Pintelon L, and Decre W Orienting safety assurance with outcomes of hazard analysis and risk assessment: a review of the ISO 15066 standard for collaborative robot systems Saf. Sci. 2020 129 104832

[227]

Wan N, Li L, Ye C, and Wang B Risk assessment in intelligent manufacturing process: a case study of an optical cable automatic arranging robot IEEE Access 2019 7 105892-105901

[228]

George G and Thampi SM Vulnerability-based risk assessment and mitigation strategies for edge devices in the internet of things Pervasive Mob. Comput. 2019 59 101068

[229]

Huang, Y.-L., Sun, W.-L., Tang, Y.-H.: 3aram: a 3-layer AHP-based risk assessment model and its implementation for an industrial IoT cloud. In: 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C), pp. 450–457. IEEE (2019)

[230]

Radanliev P, De Roure DC, Nurse JRC, Montalvo RM, Cannady S, Santos O, Burnap P, Maple C, et al. Future developments in standardisation of cyber risk in the internet of things (iot) SN Appl. Sci. 2020 2 2 169

[231]

Lv, Z., Yang, H., Singh, A.K., Manogaran, G., Lv, H.: Trustworthiness in industrial IoT systems based on artificial intelligence. IEEE Trans. Ind. Inform. (2020)

[232]

Afzaliseresht N, Miao Y, Michalska S, Liu Q, and Wang H From logs to stories: human-centred data mining for cyber threat intelligence IEEE Access 2020 8 19089-19099

[233]

Koloveas, P., Chantzios, T., Tryfonopoulos, C., Skiadopoulos, S.: A crawler architecture for harvesting the clear, social, and dark web for IoT-related cyber-threat intelligence. In: 2019 IEEE World Congress on Services (SERVICES), vol. 2642, pp. 3–8. IEEE (2019)

[234]

Xu, Z., Parizi, R.M., Hammoudeh, M., Loyola-González, O.: Cyber Security Intelligence and Analytics: Proceedings of the 2020 International Conference on Cyber Security Intelligence and Analytics (CSIA 2020), vol. 2, 1147. Springer (2020)

[235]

Gupta S, Sabitha AS, and Punhani R Cyber security threat intelligence using data mining techniques and artificial intelligence Int. J. Recent Technol. Eng. 2019 8 6133-6140

[236]

De Cubber, G., Doroftei, D., Rudin, K., Berns, K., Matos, A., Serrano, D., Sanchez, J., Govindaraj, S., Bedkowski, J., Roda, R., et al.: Introduction to the use of robotic tools for search and rescue (2017)

[237]

Davahlia A, Shamsib M, and Abaeic G A lightweight anomaly detection model using SVM for WSNs in IoT through a hybrid feature selection algorithm based on GA and GWO J. Comput. Secur. 2020 7 1 63-79

[238]

Pham, V., Seo, E., Chung, T.-M.: Lightweight convolutional neural network based intrusion detection system. J. Commun. 15(11) (2020)

[239]

He, H., Gray, J., Cangelosi, A., Meng, Q., McGinnity, T.M., Mehnen, J.: The challenges and opportunities of artificial intelligence in implementing trustworthy robotics and autonomous systems. In: 3rd International Conference on Intelligent Robotic and Control Engineering (2020)

[240]

Soe YN, Feng Y, Santosa PI, Hartanto R, and Sakurai K Towards a lightweight detection system for cyber attacks in the IoT environment using corresponding features Electronics 2020 9 1 144

[241]

Sethumadhavan S, Waksman A, Suozzo M, Huang Y, and Eum J Trustworthy hardware from untrusted components Commun. ACM 2015 58 9 60-71

[242]

Huffmire, T., Brotherton, B., Wang, G., Sherwood, T., Kastner, R., Levin, T., Nguyen, T., Irvine, C.: Moats and drawbridges: an isolation primitive for reconfigurable hardware based systems. In: 2007 IEEE Symposium on Security and Privacy (SP), pp. 281–295. IEEE (2007)

[243]

Waksman, A., Sethumadhavan, S.: Tamper evident microprocessors. In: 2010 IEEE Symposium on Security and Privacy (SP), pp. 173–188. IEEE (2010)

[244]

Agrawal, D., Baktir, S., Karakoyunlu, D., Rohatgi, P., Sunar, B.: Trojan detection using ic fingerprinting. In: IEEE Symposium on Security and Privacy, 2007. SP’07, pp. 296–310. IEEE (2007)

[245]

Pike, L., Hickey, P., Elliott, T., Mertens, E., Tomb, A.: Trackos: a security-aware real-time operating system. In: International Conference on Runtime Verification, pp. 302–317. Springer (2016)

[246]

Abera, T., Asokan, N., Davi, L., Ekberg, J.-E., Nyman, T., Paverd, A., Sadeghi, A.-R., Tsudik, G.: C-flat: control-flow attestation for embedded systems software. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pp. 743–754. ACM (2016)

[247]

Wang, H., Zhang, C., Song, Y., Pang, B.: Robot arm perceptive exploration based significant slam in search and rescue environment. Int. J. Robot. Autom. 33(4) (2018)

[248]

Romero, M., Frey, B., Southern, C., Abowd, G.D.: Brailletouch: designing a mobile eyes-free soft keyboard. In: Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services, pp. 707–709. ACM (2011)

[249]

Joint Task Force Transformation Initiative et al.: Guide for conducting risk assessments. Special Publication (NIST SP)-800-30 Rev 1 (2012)

[250]

Kriaa S, Pietre-Cambacedes L, Bouissou M, and Halgand Y A survey of approaches combining safety and security for industrial control systems Reliab. Eng. Syst. Saf. 2015 139 156-178

[251]

McLean, I., Szymanski, B., Bivens, A.: Methodology of risk assessment in mobile agent system design. In: Information Assurance Workshop, 2003. IEEE Systems, Man and Cybernetics Society, pp. 35–42. IEEE (2003)

[252]

Guiochet, J., Martin-Guillerez, D., Powell, D.: Experience with model-based user-centered risk assessment for service robots. In: 2010 IEEE 12th International Symposium on High-Assurance Systems Engineering (HASE), pp. 104–113. IEEE (2010)

[253]

Wagner HJ, Alvarez M, Kyjanek O, Bhiri Z, Buck M, and Menges A Flexible and transportable robotic timber construction platform-tim Autom. Constr. 2020 120 103400

[254]

Diab M, Pomarlan M, Beßler D, Akbari A, Rosell J, Bateman J, and Beetz M Skillman-a skill-based robotic manipulation framework based on perception and reasoning Robot. Auton. Syst. 2020 134 103653

[255]

Choi, H., Kate, S., Aafer, Y., Zhang, X., Xu, D.: Software-based realtime recovery from sensor attacks on robotic vehicles. In: 23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2020), pp. 349–364 (2020)

[256]

Beaudoin L, Avanthey L, and Villard C Porting ardupilot to esp32: towards a universal open-source architecture for agile and easily replicable multi-domains mapping robots Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2020 43 933-939

[257]

Huang, Y., Wang, W., Wang, Y., Jiang, T., Zhang, Q.: Lightweight sybil-resilient multi-robot networks by multipath manipulation. In: IEEE INFOCOM 2020-IEEE Conference on Computer Communications, pp. 2185–2193. IEEE (2020)

[258]

Wallhoff, F.: Fgnet-facial expression and emotion database. Technische Universität München (2004)

[259]

Johnson NF and Jajodia S Exploring steganography: seeing the unseen Computer 1998 31 2 26-34

[260]

Douglas M, Bailey K, Leeney M, and Curran K An overview of steganography techniques applied to the protection of biometric data Multimed. Tools Appl. 2018 77 13 17333-17373

[261]

Woodward, J.D., Jr., Horn, C., Gatune, J., Thomas, A.: Biometrics: a look at facial recognition. Technical report, Rand Corp Santa Monica, CA (2003)

[262]

Taupin JM Using forensic DNA evidence at trial: a case study approach 2016 Boca Raton CRC Press

[263]

Jain AK, Ross A, and Prabhakar S An introduction to biometric recognition IEEE Trans. Circuits Syst. Video Technol. 2004 14 1 4-20

[264]

George, J.P.: Development of efficient biometric recognition algorithms based on fingerprint and face. Ph.D. thesis, Christ University (2012)

[265]

Al-Ani MS and Rajab MA Biometrics hand geometry using discrete cosine transform (DCT) Sci. Technol. 2013 3 4 112-117

[266]

Jain, A.K., Kumar, A.: Biometric recognition: an overview. In: Second Generation Biometrics: The Ethical, Legal and Social Context, pp. 49–79. Springer (2012)

[267]

Wei X, Wang T, Tang C, and Fan J Collaborative mobile jammer tracking in multi-hop wireless network Future Gener. Comput. Syst. 2018 78 1027-1039

[268]

Nguyen, M.-H.: The relationship between password-authenticated key exchange and other cryptographic primitives. In: Theory of Cryptography Conference, pp. 457–475. Springer (2005)

[269]

Lamport L Password authentication with insecure communication Commun. ACM 1981 24 11 770-772

[270]

Song R Advanced smart card based password authentication protocol Comput. Stand. Interfaces 2010 32 5–6 321-325

[271]

Chaudhry SA, Farash MS, Naqvi H, and Sher M A secure and efficient authenticated encryption for electronic payment systems using elliptic curve cryptography Electron. Commer. Res. 2016 16 1 113-139

[272]

He D, Gao Y, Chan S, Chen C, and Jiajun B An enhanced two-factor user authentication scheme in wireless sensor networks Ad Hoc Sens. Wirel. Netw. 2010 10 4 361-371

[273]

Yeh H-L, Chen T-H, Liu P-C, Kim T-H, and Wei H-W A secured authentication protocol for wireless sensor networks using elliptic curves cryptography Sensors 2011 11 5 4767-4779

[274]

Chen T-H and Shih W-K A robust mutual authentication protocol for wireless sensor networks ETRI J. 2010 32 5 704-712

[275]

Kim J, Lee D, Jeon W, Lee Y, and Won D Security analysis and improvements of two-factor mutual authentication with key agreement in wireless sensor networks Sensors 2014 14 4 6443-6462

[276]

Xue K, Ma C, Hong P, and Ding R A temporal-credential-based mutual authentication and key agreement scheme for wireless sensor networks J. Netw. Comput. Appl. 2013 36 1 316-323

[277]

Wang, D., Li, W., Wang, P.: Measuring two-factor authentication schemes for real-time data access in industrial wireless sensor networks. IEEE Trans. Ind. Inform. (2018)

[278]

Li C-T, Weng C-Y, and Lee C-C An advanced temporal credential-based security scheme with mutual authentication and key agreement for wireless sensor networks Sensors 2013 13 8 9589-9603

[279]

Gope P, Hwang T, et al. A realistic lightweight anonymous authentication protocol for securing real-time application data access in wireless sensor networks IEEE Trans. Ind. Electron. 2016 63 11 7124-7132

[280]

Jiang Q, Ma J, Xiang L, and Tian Y An efficient two-factor user authentication scheme with unlinkability for wireless sensor networks Peer-to-peer Netw. Appl. 2015 8 6 1070-1081

[281]

Fan W, Lili X, Kumari S, and Li X A new and secure authentication scheme for wireless sensor networks with formal proof Peer-to-Peer Netw. Appl. 2017 10 1 16-30

[282]

Amin R and Biswas GP A secure light weight scheme for user authentication and key agreement in multi-gateway based wireless sensor networks Ad Hoc Netw. 2016 36 58-80

[283]

Srinivas J, Mukhopadhyay S, and Mishra D Secure and efficient user authentication scheme for multi-gateway wireless sensor networks Ad Hoc Netw. 2017 54 147-169

[284]

González Muñiz, M., Laud, P.: On the (im) possibility of perennial message recognition protocols without public-key cryptography. In: Proceedings of the 2011 ACM Symposium on Applied Computing, pp. 1510–1515. ACM (2011)

[285]

Kumar P, Choudhury AJ, Sain M, Lee S-G, and Lee H-J Ruasn: a robust user authentication framework for wireless sensor networks Sensors 2011 11 5 5020-5046

[286]

Eisenbarth T, Kumar S, Paar C, Poschmann A, and Uhsadel L A survey of lightweight-cryptography implementations IEEE Des. Test Comput. 2007 6 522-533

[287]

De Canniere, C., Dunkelman, O., Knežević, M.: Katan and ktantan—a family of small and efficient hardware-oriented block ciphers. In: Cryptographic Hardware and Embedded Systems-CHES 2009, pp. 272–288. Springer (2009)

[288]

Gong, Z., Nikova, S., Law, Y.W.: Klein: a new family of lightweight block ciphers. In: International Workshop on Radio Frequency Identification: Security and Privacy Issues, pp. 1–18. Springer (2011)

[289]

Lim, C.H., Korkishko, T.: mcrypton—a lightweight block cipher for security of low-cost rfid tags and sensors. In: International Workshop on Information Security Applications, pp. 243–258. Springer (2005)

[290]

Shibutani, K., Isobe, T., Hiwatari, H., Mitsuda, A., Akishita, T., Shirai, T.: Piccolo: an ultra-lightweight blockcipher. In: International Workshop on Cryptographic Hardware and Embedded Systems, pp. 342–357. Springer (2011)

[291]

Bogdanov, A., Knudsen, L.R., Leander, G., Paar, C., Poschmann, A., Robshaw, M.J.B., Seurin, Y., Vikkelsoe, C.: Present: an ultra-lightweight block cipher. In: International Workshop on Cryptographic Hardware and Embedded Systems, pp. 450–466. Springer (2007)

[292]

Suzaki, T., Minematsu, K., Morioka, S., Kobayashi, E.: A lightweight block cipher for multiple platforms. In: International Conference on Selected Areas in Cryptography, pp. 339–354. Springer (2012)

[293]

Yap, H., Khoo, K., Poschmann, A., Henricksen, M.: Epcbc-a block cipher suitable for electronic product code encryption. In: International Conference on Cryptology and Network Security, pp. 76–97. Springer (2011)

[294]

Dworkin, M.: Recommendation for block cipher modes of operation. Methods and techniques. Technical report, National Inst of Standards and Technology, Gaithersburg, MD, Computer Security Div (2001)

[295]

Breiling, B., Dieber, B., Schartner, P.: Secure communication for the robot operating system. In: 2017 Annual IEEE International Systems Conference (SysCon), pp. 1–6. IEEE (2017)

[296]

Hussein, A., Elhajj, I.H., Chehab, A., Kayssi, A.: Securing diameter: comparing tls, dtls, and ipsec. In: 2016 IEEE International Multidisciplinary Conference on Engineering Technology (IMCET), pp. 1–8. IEEE (2016)

[297]

Dieber, B., Kacianka, S., Rass, S., Schartner, P.: Application-level security for ros-based applications. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4477–4482. IEEE (2016)

[298]

Hussaini, S.: Cyber security in cloud using blowfish encryption. Int. J. Inf. Technol. (IJIT), 6(5) (2020)

[299]

Tian, N.: Cloud-edge hybrid robotic systems for physical human robot interactions. Ph.D. thesis, UC Berkeley (2020)

[300]

Chavhan, S., Doriya, R.: Secured map building using elliptic curve integrated encryption scheme and kerberos for cloud-based robots. In: 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), pp. 157–164. IEEE (2020)

[301]

Strobel V, Ferrer EC, and Dorigo M Blockchain technology secures robot swarms: a comparison of consensus protocols and their resilience to byzantine robots Front. Robot. AI 2020 7 54

[302]

Alcaraz, C., Rubio, J.E., Lopez, J.: Blockchain-assisted access for federated smart grid domains: coupling and features. J. Parallel Distrib. Comput. (2020)

[303]

Fagiolini, A., Pellinacci, M., Valenti, G., Dini, G., Bicchi, A.: Consensus-based distributed intrusion detection for multi-robot systems. In: IEEE International Conference on Robotics and Automation, 2008. ICRA 2008, pp. 120–127. IEEE (2008)

[304]

Reategui, E.B., Campbell, J.: A classification system for credit card transactions. In: European Workshop on Advances in Case-Based Reasoning, pp. 280–291. Springer (1994)

[305]

Bonifacio, J.M., Cansian, A.M., De Carvalho, A.C.P.L.F., Moreira, E.S.: Neural networks applied in intrusion detection systems. In: The 1998 IEEE International Joint Conference on Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence, vol. 1, pp. 205–210. IEEE (1998)

[306]

Yeung, D.-Y., Chow, C.: Parzen-window network intrusion detectors. In: Object Recognition Supported by User Interaction for Service Robots, vol. 4, pp. 385–388. IEEE (2002)

[307]

Vigna, G., Robertson, W., Kher, V., Kemmerer, R.A.: A stateful intrusion detection system for world-wide web servers. In: Null, p. 34. IEEE (2003)

[308]

Onat, I., Miri, A.: An intrusion detection system for wireless sensor networks. In: IEEE International Conference on Wireless and Mobile Computing, Networking And Communications, 2005.(WiMob’2005), vol. 3, pp. 253–259. IEEE (2005)

[309]

Gudadhe, M., Prasad, P., Wankhade, L.K.: A new data mining based network intrusion detection model. In: 2010 International Conference on Computer and Communication Technology (ICCCT), pp. 731–735. IEEE (2010)

[310]

Om, H., Kundu, A.: A hybrid system for reducing the false alarm rate of anomaly intrusion detection system. In: 2012 1st International Conference on Recent Advances in Information Technology (RAIT), pp. 131–136. IEEE (2012)

[311]

Rath M and Pattanayak BK Security protocol with ids framework using mobile agent in robotic manet Int. J. Inf. Secur. Privacy (IJISP) 2019 13 1 46-58

[312]

Rivera, S., Iannillo, A.K., et al.: Ros-immunity: integrated approach for the security of ros-enabled robotic systems (2020)

[313]

Zhou, Y., Mazzuchi, T.A., Sarkani, S.: M-adaboost-a based ensemble system for network intrusion detection. Expert Syst. Appl. 162 (2020)

[314]

Gorbenko, A., Popov, V.: Abnormal behavioral pattern detection in closed-loop robotic systems for zero-day deceptive threats. In: 2020 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), pp. 1–6. IEEE (2020)

[315]

Almalawi A, Fahad A, Tari Z, Khan AI, Alzahrani N, Bakhsh ST, Alassafi MO, Alshdadi A, and Qaiyum S Add-on anomaly threshold technique for improving unsupervised intrusion detection on scada data Electronics 2020 9 6 1017

[316]

Spitzner L Honeypots: Tracking Hackers 2003 Reading Addison-Wesley

[317]

Zhang, F., Zhou, S., Qin, Z., Liu, J.: Honeypot: a supplemented active defense system for network security. In: Proceedings of the Fourth International Conference on Parallel and Distributed Computing, Applications and Technologies, 2003. PDCAT’2003, pp. 231–235. IEEE (2003)

[318]

Irvene C, Formby D, Litchfield S, and Beyah R Honeybot: a honeypot for robotic systems Proc. IEEE 2018 106 1 61-70

[319]

Ranum, M.: Backofficer friendly (bof)

[320]

Spitzner, L.: Specter: a commercial honeypot solution for windows. Acesso em 26(08) (2003)

[321]

Provos, N.: Honeyd-a virtual honeypot daemon. In: 10th DFN-CERT Workshop, Hamburg, Germany, vol. 2, p. 4 (2003)

[322]

La, Q.D., Quek, T.Q.S., Lee, J.: A game theoretic model for enabling honeypots in IoT networks. In: 2016 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2016)

[323]

Spitzner L The honeynet project: trapping the hackers IEEE Secur. Privacy 2003 99 2 15-23

[324]

Terra, A., Riaz, H., Raizer, K., Hata, A., Inam, R.: Safety vs. efficiency: Ai-based risk mitigation in collaborative robotics. In: 2020 6th International Conference on Control, Automation and Robotics (ICCAR), pp. 151–160. IEEE (2020)

[325]

Wang, C., Tok, Y.C., Poolat, R., Chattopadhyay, S., Elara, M.R.: How to secure autonomous mobile robots? an approach with fuzzing, detection and mitigation. J. Syst. Archit. 101838 (2020)

[326]

Bykovsky AY Heterogeneous network architecture for integration of AI and quantum optics by means of multiple-valued logic Quantum Rep. 2020 2 1 126-165

[327]

Alamer, A.: A secure anonymous tracing fog-assisted method for the internet of robotic things. Library Hi Tech (2020)

[328]

Szalachowski P, Ksiezopolski B, and Kotulski Z Cmac, ccm and gcm/gmac: advanced modes of operation of symmetric block ciphers in wireless sensor networks Inf. Process. Lett. 2010 110 7 247-251

[329]

Abeykoon, I., Feng, X.: A forensic investigation of the robot operating system. In: 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), pp. 851–857. IEEE (2017)

[330]

Erbacher, R.F., Christiansen, K., Sundberg, A., et al.: Visual network forensic techniques and processes. In: 1st Annual Symposium on Information Assurance: Intrusion Detection and Prevention, p. 72 (2006)

[331]

Noura HN, Melki R, Chehab A, and Fernandez JH Efficient and robust data availability solution for hybrid plc/rf systems Comput. Netw. 2021 185 107675

[332]

Chigan, C., Li, L., Ye, Y.: Resource-aware self-adaptive security provisioning in mobile ad hoc networks. In: 2005 IEEE Wireless Communications and Networking Conference, vol. 4, pp. 2118–2124. IEEE (2005)

[333]

Bethencourt, J., Sahai, A., Waters, B.: Ciphertext-policy attribute-based encryption. In: IEEE Symposium on Security and Privacy, 2007. SP’07, pp. 321–334. IEEE (2007)

[334]

Needham, R.M., Wheeler, D.J.: Tea extensions. Report (Cambridge University, Cambridge, UK, 1997) Google Scholar (1997)

[335]

Hu, W., Corke, P., Shih, W.C., Overs, L.: secfleck: a public key technology platform for wireless sensor networks. In: European Conference on Wireless Sensor Networks, pp. 296–311. Springer (2009)

[336]

Hu W, Tan H, Corke P, Shih WC, and Jha S Toward trusted wireless sensor networks ACM Trans. Sens. Netw. (TOSN) 2010 7 1 5

[337]

Touati, L., Challal, Y., Bouabdallah, A.: C-cp-abe: cooperative ciphertext policy attribute-based encryption for the internet of things. In: 2014 International Conference on Advanced Networking Distributed Systems and Applications (INDS), pp. 64–69. IEEE (2014)

[338]

Touati, L., Challal, Y.: Collaborative kp-abe for cloud-based internet of things applications. In: 2016 IEEE International Conference on Communications (ICC), pp. 1–7. IEEE (2016)

[339]

Goyal, V., Pandey, O., Sahai, A., Waters, B.: Attribute-based encryption for fine-grained access control of encrypted data. In: Proceedings of the 13th ACM Conference on Computer and communications security, pp. 89–98. ACM (2006)

[340]

Hohenberger, S., Lysyanskaya, A.: How to securely outsource cryptographic computations. In: Theory of Cryptography Conference, pp. 264–282. Springer (2005)

[341]

Even S, Goldreich O, and Micali S On-line/off-line digital signatures J. Cryptol. 1996 9 1 35-67

[342]

Laih C-S and Kuo W-C New signature schemes based on factoring and discrete logarithms IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 1997 80 1 46-53

[343]

Courtois, N.T., Finiasz, M., Sendrier, N.: How to achieve a Mceliece-based digital signature scheme. In: International Conference on the Theory and Application of Cryptology and Information Security, pp. 157–174. Springer (2001)

[344]

Koblitz N Elliptic curve cryptosystems Math. Comput. 1987 48 177 203-209

[345]

Hoffstein, J., Pipher, J., Silverman, J.H.: Ntru: a ring-based public key cryptosystem. In: International Algorithmic Number Theory Symposium, pp. 267–288. Springer (1998)

[346]

Noura, H.N., Melki, R., Chehab, A.: Efficient data confidentiality scheme for 5g wireless NOMA communications. J. Inf. Secur. Appl. 58 (2021)

[347]

Noura HN, Melki R, Kanj R, and Chehab A Secure MIMO d2d communication based on a lightweight and robust PLS cipher scheme Wirel. Netw. 2021 27 1 557-574

[348]

Trappe W, Howard R, and Moore RS Low-energy security: limits and opportunities in the internet of things IEEE Secur. Privacy 2015 13 1 14-21

[349]

Mukherjee A Physical-layer security in the internet of things: sensing and communication confidentiality under resource constraints Proc. IEEE 2015 103 10 1747-1761

[350]

Noura, H.N., Melki, R., Chehab, A., Mansour, M.M., Martin, S.: Efficient and secure physical encryption scheme for low-power wireless m2m devices. In: 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC), pp. 1267–1272. IEEE (2018)

[351]

Melki R, Noura HN, Mansour MM, and Chehab A An efficient OFDM-based encryption scheme using a dynamic key approach IEEE Internet of Things J. 2018 6 1 361-378

[352]

Noura, H.N., Melki, R., Chehab, A., Hernandez Fernandez, J.: Efficient and secure message authentication algorithm at the physical layer. Wirel. Netw. 1–15 (2020)

[353]

Bellare, M., Canetti, R., Krawczyk, H.: Keying hash functions for message authentication. In: Annual International Cryptology Conference, pp. 1–15. Springer (1996)

[354]

Noura HN, Salman O, Chehab A, and Couturier R Distlog: a distributed logging scheme for IoT forensics Ad Hoc Netw. 2020 98 102061

[355]

Melki R, Noura HN, and Chehab A Lightweight multi-factor mutual authentication protocol for IoT devices Int. J. Inf. Secur. 2019 19 1-16

[356]

Noura, H.N., Melki, R., Chehab, A.: Secure and lightweight mutual multi-factor authentication for IoT communication systems. In: 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), pp. 1–7. IEEE (2019)

[357]

Noura, H.N., Salman, O., Couturier, R., Chehab, A.: Novel one round message authentication scheme for constrained IoT devices. J. Ambient Intell. Hum. Comput. 1–17 (2021)

[358]

Noura HN, Noura M, Salman O, Couturier R, and Chehab A Efficient & secure image availability and content protection Multimed. Tools Appl. 2020 79 22869-22904

[359]

Noura HN, Chehab A, Sleem L, Noura M, Couturier R, and Mansour MM One round cipher algorithm for multimedia IoT devices Multimed. Tools Appl. 2018 77 1-31

[360]

Noura, H., Chehab, A., Couturier, R.: Lightweight dynamic key-dependent and flexible cipher scheme for IoT devices. In: 2019 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–8. IEEE (2019)

[361]

Noura, H.N., Couturier, R., Pham, C., Chehab, A.: Lightweight stream cipher scheme for resource-constrained IoT devices. In: 2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 1–8. IEEE (2019)

[362]

Noura, H.N., Chehab, A., Couturier, R.: Overview of efficient symmetric cryptography: dynamic vs static approaches. In: 2020 8th International Symposium on Digital Forensics and Security (ISDFS), pp. 1–6. IEEE (2020)

[363]

Noura, H.N., Melki, R., Malli, M., Chehab, A.: Lightweight and secure cipher scheme for multi-homed systems. Wirel. Netw. 1–18

[364]

Noura HN, Salman O, Chehab A, and Couturier R Preserving data security in distributed fog computing Ad Hoc Netw. 2019 94 101937

[365]

Noura, H.N., Salman, O., Kaaniche, N., Sklavos, N., Chehab, A., Couturier, R.: Tresc: Towards redesigning existing symmetric ciphers. Microprocess. Microsyst. 103478 (2020)

[366]

Fawaz Z, Noura HN, and Mostefaoui A Securing jpeg-2000 images in constrained environments: a dynamic approach Multimed. Syst. 2018 24 6 669-694

[367]

Mostefaoui A, Noura HN, and Fawaz Z An integrated multimedia data reduction and content confidentiality approach for limited networked devices Ad Hoc Netw. 2015 32 81-97

[368]

Salman, O., Elhajj, I.H., Chehab, A., Kayssi, A.: A multi-level internet traffic classifier using deep learning. In: 2018 9th International Conference on the Network of the Future (NOF), pp. 68–75 (2018)

[369]

Salman, O., Chaddad, L., Elhajj, I.H., Chehab, A., Kayssi, A.: Pushing intelligence to the network edge. In: 2018 Fifth International Conference on Software Defined Systems (SDS), pp. 87–92 (2018)

Cited By

Blancaflor EOrdonez BPajutrao DVerano K(2024)Enhancing Online Privacy and Security through Proxy Chaining in Kali Linux: A Comprehensive AnalysisProceedings of the 2024 8th International Conference on E-Commerce, E-Business, and E-Government10.1145/3675585.3675593(51-55)Online publication date: 28-May-2024
https://dl.acm.org/doi/10.1145/3675585.3675593
Bransky KSweetser PCaldwell SFletcher KGrollman DBroadbent EJu WSoh HWilliams T(2024)Mind-Body-Identity: A Scoping Review of Multi-EmbodimentProceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610977.3634922(65-75)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610977.3634922
Kong RChen H(2024)CSI-RFF: Leveraging Micro-Signals on CSI for RF Fingerprinting of Commodity WiFiIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.339637519(5301-5315)Online publication date: 2-May-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3396375
Show More Cited By

Index Terms

Robotics cyber security: vulnerabilities, attacks, countermeasures, and recommendations

Index terms have been assigned to the content through auto-classification.

Recommendations

A vulnerability-centric requirements engineering framework: analyzing security attacks, countermeasures, and requirements based on vulnerabilities
Special Issue on RE'09: Security Requirements Engineering; Guest Editors: Eric Dubois and Haralambos Mouratidis

Many security breaches occur because of exploitation of vulnerabilities within the system. Vulnerabilities are weaknesses in the requirements, design, and implementation, which attackers exploit to compromise the system. This paper proposes a ...
Security beyond cybersecurity: side-channel attacks against non-cyber systems and their countermeasures
Abstract
Side-channels are unintended pathways within target systems that leak internal information, exploitable via side-channel attack techniques that extract the target information, compromising the system’s security and privacy. Side-channel attacks ...
Countermeasures for timing-based side-channel attacks against shared, modern computing hardware

There are several vulnerabilities in computing systems hardware that can be exploited by attackers to carry out devastating microarchitectural timing-based side-channel attacks against these systems and as a result compromise the security of the users of ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image International Journal of Information Security

International Journal of Information Security Volume 21, Issue 1

Feb 2022

156 pages

ISSN:1615-5262

EISSN:1615-5270

Issue’s Table of Contents

© The Author(s), under exclusive licence to Springer-Verlag GmbH, DE 2021.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 February 2022

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 01 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Blancaflor EOrdonez BPajutrao DVerano K(2024)Enhancing Online Privacy and Security through Proxy Chaining in Kali Linux: A Comprehensive AnalysisProceedings of the 2024 8th International Conference on E-Commerce, E-Business, and E-Government10.1145/3675585.3675593(51-55)Online publication date: 28-May-2024
https://dl.acm.org/doi/10.1145/3675585.3675593
Bransky KSweetser PCaldwell SFletcher KGrollman DBroadbent EJu WSoh HWilliams T(2024)Mind-Body-Identity: A Scoping Review of Multi-EmbodimentProceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610977.3634922(65-75)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610977.3634922
Kong RChen H(2024)CSI-RFF: Leveraging Micro-Signals on CSI for RF Fingerprinting of Commodity WiFiIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.339637519(5301-5315)Online publication date: 2-May-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3396375
Mohammed AFourati LFakhrudeen A(2024)Comprehensive systematic review of intelligent approaches in UAV-based intrusion detection, blockchain, and network securityComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.110140239:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.comnet.2023.110140
Rasouli SGhafurian MNilsen EDautenhahn K(2024)University Students’ Opinions on Using Intelligent Agents to Cope with Stress and Anxiety in Social SituationsComputers in Human Behavior10.1016/j.chb.2023.108072153:COnline publication date: 12-Apr-2024
https://dl.acm.org/doi/10.1016/j.chb.2023.108072
Aurangzeb SAleem MKhan MAnwar HSiddique M(2024)Cybersecurity for autonomous vehicles against malware attacks in smart-citiesCluster Computing10.1007/s10586-023-04114-727:3(3363-3378)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10586-023-04114-7
Browne TAbedin MChowdhury M(2024)A systematic review on research utilising artificial intelligence for open source intelligence (OSINT) applicationsInternational Journal of Information Security10.1007/s10207-024-00868-223:4(2911-2938)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10207-024-00868-2
Krishna HSekhar K(2024)Enhancing security in IIoT applications through efficient quantum key exchange and advanced encryption standardSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09585-928:3(2671-2681)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s00500-023-09585-9
Wardega Kvon Hippel MTron RNita-Rotaru CLi WAgmon NAn BRicci AYeoh W(2023)Byzantine Resilience at Swarm Scale: A Decentralized Blocklist Protocol from Inter-robot AccusationsProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598795(1430-1438)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598795
Hong AMalinovsky PDamodaran S(2023)Towards Attack Detection in Multimodal Cyber-Physical Systems with Sticky HDP-HMM based Time Series AnalysisDigital Threats: Research and Practice10.1145/3604434Online publication date: 17-Jun-2023
https://dl.acm.org/doi/10.1145/3604434
Show More Cited By

View Options

View options

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 Issue’s Table of Contents