Security in cyber physical systems: Transformation and challenges
Abstract
Network technology has significantly improved due to the growing use of Cyber-Physical Systems (CPS) in various industries, including healthcare, transportation, and communication. The efficiency of these domains has increased overall due to the transmission of sensor data to the cloud and its use by various apps. However, increased data transfer increases the risk of unauthorized modification and data breaches. The degree of risk varies per domain, and security is a crucial area of concentration to mitigate these concerns. Significant developments in network technology have resulted from the growing use of Cyber-Physical Systems (CPS) in various industries, including healthcare, transportation, and communication. The efficiency of these fields has increased overall due to sensor data being sent to the cloud and used by various applications. However, data breaches and unauthorized alteration are risks that come with increased data flow. Depending on the domain, the risk level varies, and security is a key concern in addressing these concerns.
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1. Rajkumar R (Raj), Lee I, Sha L, et al. Cyber-physical systems. Proceedings of the 47th Design Automation Conference. Published online June 13, 2010. doi: 10.1145/1837274.1837461
2. Kaur A, Chatterjee JM. Applications of Cyber‐Physical Systems. Cyber‐Physical Systems. Published online July 2022: 289-310. doi: 10.1002/9781119836636.ch13
3. Caviglia R, Gaggero G, Portomauro G, et al. An SDR-Based Cybersecurity Verification Framework for Smart Agricultural Machines. IEEE Access. 2023, 11: 54210-54220. doi: 10.1109/access.2023.3282169
4. Gaggero GB, Fausto A, Patrone F, et al. A Framework for Network Security Verification of Automated Vehicles in the Agricultural Domain. 2022 26th International Conference Electronics. Published online June 13, 2022. doi: 10.1109/ieeeconf55059.2022.9810440
5. Molina E, Jacob E. Software-defined networking in cyber-physical systems: A survey. Computers & Electrical Engineering. 2018, 66: 407-419. doi: 10.1016/j.compeleceng.2017.05.013
6. Calvaresi D, Marinoni M, Sturm A, et al. The challenge of real-time multi-agent systems for enabling IoT and CPS. Proceedings of the International Conference on Web Intelligence. Published online August 23, 2017. doi: 10.1145/3106426.3106518
7. Zografopoulos I, Ospina J, Liu X, et al. Cyber-Physical Energy Systems Security: Threat Modeling, Risk Assessment, Resources, Metrics, and Case Studies. IEEE Access. 2021, 9: 29775-29818. doi: 10.1109/access.2021.3058403
8. Hasan MK, Habib AA, Shukur Z, et al. Review on cyber-physical and cyber-security system in smart grid: Standards, protocols, constraints, and recommendations. Journal of Network and Computer Applications. 2023, 209: 103540. doi: 10.1016/j.jnca.2022.103540
9. Gupta A, Singh A. A Comprehensive Survey on Cyber-Physical Systems Towards Healthcare 4.0. SN Computer Science. 2023, 4(2). doi: 10.1007/s42979-023-01669-5
10. Tushar W, Yuen C, Saha TK, et al. A Survey of Cyber-Physical Systems From a Game-Theoretic Perspective. IEEE Access. 2023, 11: 9799-9834. doi: 10.1109/access.2023.3239834
11. Cassottana B, Roomi MM, Mashima D, et al. Resilience analysis of cyber‐physical systems: A review of models and methods. Risk Analysis. 2023, 43(11): 2359-2379. doi: 10.1111/risa.14089
12. Duo W, Zhou M, Abusorrah A. A Survey of Cyber Attacks on Cyber Physical Systems: Recent Advances and Challenges. IEEE/CAA Journal of Automatica Sinica. 2022, 9(5): 784-800. doi: 10.1109/jas.2022.105548
13. Bashendy M, Tantawy A, Erradi A. Intrusion response systems for cyber-physical systems: A comprehensive survey. Computers & Security. 2023, 124: 102984. doi: 10.1016/j.cose.2022.102984
14. Salau BA, Rawal A, Rawat DB. Recent Advances in Artificial Intelligence for Wireless Internet of Things and Cyber–Physical Systems: A Comprehensive Survey. IEEE Internet of Things Journal. 2022, 9(15): 12916-12930. doi: 10.1109/jiot.2022.3170449
15. Kim S, Park KJ, Lu C. A Survey on Network Security for Cyber–Physical Systems: From Threats to Resilient Design. IEEE Communications Surveys & Tutorials. 2022, 24(3): 1534-1573. doi: 10.1109/comst.2022.3187531
16. Agrawal N, Kumar R. Security Perspective Analysis of Industrial Cyber Physical Systems (I-CPS): A Decade-wide Survey. ISA Transactions. 2022, 130: 10-24. doi: 10.1016/j.isatra.2022.03.018
17. Rupprecht T, Wang Y. A survey for deep reinforcement learning in markovian cyber–physical systems: Common problems and solutions. Neural Networks. 2022, 153: 13-36. doi: 10.1016/j.neunet.2022.05.013
18. Harris JD, Quatman CE, Manring MM, et al. How to Write a Systematic Review. The American Journal of Sports Medicine. 2013, 42(11): 2761-2768. doi: 10.1177/0363546513497567
19. Pati D, Lorusso LN. How to Write a Systematic Review of the Literature. HERD: Health Environments Research & Design Journal. 2017, 11(1): 15-30. doi: 10.1177/1937586717747384
20. Nourian A, Madnick S. A Systems Theoretic Approach to the Security Threats in Cyber Physical Systems Applied to Stuxnet. IEEE Transactions on Dependable and Secure Computing. 2018, 15(1): 2-13. doi: 10.1109/tdsc.2015.2509994
21. Liu Y, Peng Y, Wang B, et al. Review on cyber-physical systems. IEEE/CAA Journal of Automatica Sinica. 2017, 4(1): 27-40. doi: 10.1109/jas.2017.7510349
22. Inderwildi O, Zhang C, Wang X, et al. The impact of intelligent cyber-physical systems on the decarbonization of energy. Energy & Environmental Science. 2020, 13(3): 744-771. doi: 10.1039/c9ee01919g
23. Ashibani Y, Mahmoud QH. Cyber physical systems security: Analysis, challenges and solutions. Computers & Security. 2017, 68: 81-97. doi: 10.1016/j.cose.2017.04.005
24. Lee J, Bagheri B, Kao HA. A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters. 2015, 3: 18-23. doi: 10.1016/j.mfglet.2014.12.001
25. Sonntag D, Zillner S, van der Smagt P, et al. Overview of the CPS for Smart Factories Project: Deep Learning, Knowledge Acquisition, Anomaly Detection and Intelligent User Interfaces. Springer Series in Wireless Technology. Published online October 13, 2016: 487-504. doi: 10.1007/978-3-319-42559-7_19
26. Zhang J, Pan L, Han QL, et al. Deep Learning Based Attack Detection for Cyber-Physical System Cybersecurity: A Survey. IEEE/CAA Journal of Automatica Sinica. 2022, 9(3): 377-391. doi: 10.1109/jas.2021.1004261
27. Alguliyev R, Imamverdiyev Y, Sukhostat L. Cyber-physical systems and their security issues. Computers in Industry. 2018, 100: 212-223. doi: 10.1016/j.compind.2018.04.017
28. Cleveland FM. Cyber security issues for Advanced Metering Infrasttructure (AMI). 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century. Published online July 2008. doi: 10.1109/pes.2008.4596535
29. Metke AR, Ekl RL. Smart Grid security technology. 2010 Innovative Smart Grid Technologies (ISGT). Published online January 2010. doi: 10.1109/isgt.2010.5434760
30. Yaacoub JPA, Salman O, Noura HN, et al. Cyber-physical systems security: Limitations, issues and future trends. Microprocessors and Microsystems. 2020, 77: 103201. doi: 10.1016/j.micpro.2020.103201
31. Kitchin R, Dodge M. The (In)Security of Smart Cities: Vulnerabilities, Risks, Mitigation, and Prevention. Journal of Urban Technology. 2017, 26(2): 47-65. doi: 10.1080/10630732.2017.1408002
32. Basan E, Mikhailova V, Shulika M. Exploring Security Testing Methods for Cyber-Physical Systems. 2022 International Siberian Conference on Control and Communications (SIBCON). Published online November 17, 2022. doi: 10.1109/sibcon56144.2022.10002880
33. Ju Y, Yang M, Chakraborty C, et al. Reliability-Security Tradeoff Analysis in mmWave Ad Hoc Based CPS. ACM Transactions on Sensor Networks. Published online February 2023. doi: 10.1145/3582556
34. Johari R, Sharma P. A Survey on Web Application Vulnerabilities (SQLIA, XSS) Exploitation and Security Engine for SQL Injection. 2012 International Conference on Communication Systems and Network Technologies. Published online May 2012. doi: 10.1109/csnt.2012.104
35. Kundankumar RS, Malathip. Cyber physical system security by splunk. i-manager’s Journal on Communication Engineering and Systems. 2020, 9(2): 41. doi: 10.26634/jcs.9.2.18115
36. Zhou J, Luo Y, Liu Y, et al. Eavesdropping Strategies for Remote State Estimation Under Communication Constraints. IEEE Transactions on Information Forensics and Security. 2023, 18: 2250-2261. doi: 10.1109/tifs.2023.3265343
37. Golchha R, Lachure J, Doriya R. Fog Enabled Cyber Physical System Authentication and Data Security using Lattice and Quantum AES Cryptography. International Journal of Computing and Digital Systems. 2023, 13(1): 267-275. doi: 10.12785/ijcds/130122
38. Wu S, Jiang Y, Luo H, et al. Deep learning-based defense and detection scheme against eavesdropping and typical cyber-physical attacks. 2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS). Published online December 17, 2021. doi: 10.1109/safeprocess52771.2021.9693596
39. Gao J, Xu W, Kanhere S, et al. A Novel Model-Based Security Scheme for LoRa Key Generation. Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021). Published online May 18, 2021. doi: 10.1145/3412382.3458256
40. Umer M, Sadiq S, Karamti H, et al. Deep Learning-Based Intrusion Detection Methods in Cyber-Physical Systems: Challenges and Future Trends. Electronics. 2022, 11(20): 3326. doi: 10.3390/electronics11203326
41. Girdhar K, Singh C, Kumar Y. AI and Blockchain for Cybersecurity in Cyber-Physical Systems: Challenges and Future Research Agenda. Blockchain for Cybersecurity in Cyber-Physical Systems. Published online 2023: 185-213. doi: 10.1007/978-3-031-25506-9_10
42. Catillo M, Pecchia A, Villano U. CPS-GUARD: Intrusion detection for cyber-physical systems and IoT devices using outlier-aware deep autoencoders. Computers & Security. 2023, 129: 103210. doi: 10.1016/j.cose.2023.103210
43. Nguyen GN, Viet NHL, Elhoseny M, et al. Secure blockchain enabled Cyber–physical systems in healthcare using deep belief network with ResNet model. Journal of Parallel and Distributed Computing. 2021, 153: 150-160. doi: 10.1016/j.jpdc.2021.03.011
44. Yeboah-Ofori A, Islam S, Lee SW, et al. Cyber Threat Predictive Analytics for Improving Cyber Supply Chain Security. IEEE Access. 2021, 9: 94318-94337. doi: 10.1109/access.2021.3087109
45. Quincozes SE, Mosse D, Passos D, et al. On the Performance of GRASP-Based Feature Selection for CPS Intrusion Detection. IEEE Transactions on Network and Service Management. 2022, 19(1): 614-626. doi: 10.1109/tnsm.2021.3088763
46. Raza A, Memon S, Nizamani MA, et al. Machine Learning-Based Security Solutions for Critical Cyber-Physical Systems. 2022 10th International Symposium on Digital Forensics and Security (ISDFS). Published online June 6, 2022. doi: 10.1109/isdfs55398.2022.9800811
47. R M Seyam A, Bou Nassif A, Nasir Q, et al. Deep Learning Techniques to Detect DoS Attacks on Industrial Control Systems: A Systematic Literature Review. The 7th Annual International Conference on Arab Women in Computing in Conjunction with the 2nd Forum of Women in Research. Published online August 25, 2021. doi: 10.1145/3485557.3485577
48. Hsu YF, Ryusei A, Matsuoka M. Real Network DDoS Pattern Analysis and Detection. 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). Published online June 2022. doi: 10.1109/compsac54236.2022.00236
49. Mahmood H, Mahmood D, Shaheen Q, et al. S-DPS: An SDN-Based DDoS Protection System for Smart Grids. Chaudhry S, ed. Security and Communication Networks. 2021, 2021: 1-19. doi: 10.1155/2021/6629098
50. Daniel A, Deebalakshmi R, Thilagavathy R, et al. Optimal feature selection for malware detection in cyber physical systems using graph convolutional network. Computers and Electrical Engineering. 2023, 108: 108689. doi: 10.1016/j.compeleceng.2023.108689
51. Liu J, Tang Y, Zhao H, et al. CPS Attack Detection under Limited Local Information in Cyber Security: An Ensemble Multi-Node Multi-class Classification Approach. ACM Transactions on Sensor Networks. Published online March 6, 2023. doi: 10.1145/3585520
52. Achar S, Faruqui N, Whaiduzzaman M, et al. Cyber-Physical System Security Based on Human Activity Recognition through IoT Cloud Computing. Electronics. 2023, 12(8): 1892. doi: 10.3390/electronics12081892
53. Longari S, Pozone A, Leoni J, et al. CyFence: Securing Cyber-physical Controllers Via Trusted Execution Environment. IEEE Transactions on Emerging Topics in Computing. Published online 2023: 1-12. doi: 10.1109/tetc.2023.3268412
54. Chaitanya SMK, Choppakatla N. A novel embedded system for cyber-physical system using crypto mechanism. Multimedia Tools and Applications. 2023, 82(26): 40085-40103. doi: 10.1007/s11042-023-15172-9
55. Ji Z, Yang SH, Cao Y, et al. Harmonizing safety and security risk analysis and prevention in cyber-physical systems. Process Safety and Environmental Protection. 2021, 148: 1279-1291. doi: 10.1016/j.psep.2021.03.004
56. Rosado DG, Santos-Olmo A, Sánchez LE, et al. Managing cybersecurity risks of cyber-physical systems: The MARISMA-CPS pattern. Computers in Industry. 2022, 142: 103715. doi: 10.1016/j.compind.2022.103715
57. Machaka P, Ajayi O, Maluleke H, et al. Modelling DDoS Attacks in IoT Networks using Machine Learning. Available online: http://arxiv.org/abs/2112.05477 (accessed on 6 December 2023)
58. Ravi V, Chaganti R, Alazab M. Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system. Computers and Electrical Engineering. 2022, 102: 108156. doi: 10.1016/j.compeleceng.2022.108156
59. Lilhore UK, Simaiya S, Sandhu JK, et al. EHML: An Efficient Hybrid Machine Learning Model for Cyber Threat Forecasting in CPS. 2023 International Conference on Artificial Intelligence and Smart Communication (AISC). Published online January 27, 2023. doi: 10.1109/aisc56616.2023.10084987
60. Wolf M, Serpanos D. Safety and Security in Cyber-Physical Systems and Internet-of-Things Systems. Proceedings of the IEEE. 2018, 106(1): 9-20. doi: 10.1109/jproc.2017.2781198
61. Yang X, Shu L, Liu Y, et al. Physical Security and Safety of IoT Equipment: A Survey of Recent Advances and Opportunities. IEEE Transactions on Industrial Informatics. 2022, 18(7): 4319-4330. doi: 10.1109/tii.2022.3141408
62. Krotofil M, Larsen J, Gollmann D. The Process Matters. Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security. Published online April 14, 2015. doi: 10.1145/2714576.2714599
63. Anwar FM, Garcia L, Han X, et al. Securing Time in Untrusted Operating Systems with TimeSeal. 2019 IEEE Real-Time Systems Symposium (RTSS). Published online December 2019. doi: 10.1109/rtss46320.2019.00018
64. Wang H, Sayadi H, Sasan A, et al. Hybrid-shield. Proceedings of the 39th International Conference on Computer-Aided Design. Published online November 2, 2020. doi: 10.1145/3400302.3418783
65. Ratasich D, Khalid F, Geissler F, et al. A Roadmap Toward the Resilient Internet of Things for Cyber-Physical Systems. IEEE Access. 2019, 7: 13260-13283. doi: 10.1109/access.2019.2891969
66. Kanagala P. Effective cyber security system to secure optical data based on deep learning approach for healthcare application. Optik. 2023, 272: 170315. doi: 10.1016/j.ijleo.2022.170315
67. Abosuliman SS. Deep learning techniques for securing cyber-physical systems in supply chain 4.0. Computers and Electrical Engineering. 2023, 107: 108637. doi: 10.1016/j.compeleceng.2023.108637
68. Ramachandran A, Gayathri K, Alkhayyat A, et al. Malik R. Aquila Optimization with Machine Learning-Based Anomaly Detection Technique in Cyber-Physical Systems. Computer Systems Science and Engineering. 2023, 46(2): 2177-2194. doi: 10.32604/csse.2023.034438
69. Wu C, Pan W, Staa R, et al. Deep reinforcement learning control approach to mitigating actuator attacks. Automatica. 2023, 152: 110999. doi: 10.1016/j.automatica.2023.110999
70. Sahani N, Zhu R, Cho JH, et al. Machine Learning-based Intrusion Detection for Smart Grid Computing: A Survey. ACM Transactions on Cyber-Physical Systems. 2023, 7(2): 1-31. doi: 10.1145/3578366
71. Cai T, Jia T, Adepu S, et al. ADAM: An Adaptive DDoS Attack Mitigation Scheme in Software-Defined Cyber-Physical System. IEEE Transactions on Industrial Informatics. 2023, 19(6): 7802-7813. doi: 10.1109/tii.2023.3240586
72. Liang W, Long J, Weng TH, et al. TBRS: A trust based recommendation scheme for vehicular CPS network. Future Generation Computer Systems. 2019, 92: 383-398. doi: 10.1016/j.future.2018.09.002
73. Gholami N, Torkzaban, Baras JS. On the Importance of Trust in Next-Generation Networked CPS Systems: An AI Perspective. Available online: http://arxiv.org/abs/2104.07853 (accessed on 6 December 2023)
74. Ziegler S, Skarmeta A, Bernal J, et al. ANASTACIA: Advanced networked agents for security and trust assessment in CPS IoT architectures. 2017 Global Internet of Things Summit (GIoTS). Published online June 2017. doi: 10.1109/giots.2017.8016285
75. Liu Y, Liu A, Liu X, et al. A Trust-Based Active Detection for Cyber-Physical Security in Industrial Environments. IEEE Transactions on Industrial Informatics. 2019, 15(12): 6593-6603. doi: 10.1109/tii.2019.2931394
76. Abidi MH, Alkhalefah H, Moiduddin K, et al. Novel improved chaotic elephant herding optimization algorithm-based optimal defense resource allocation in cyber-physical systems. Soft Computing. 2022, 27(6): 2965-2980. doi: 10.1007/s00500-022-07455-4
77. Wu JMT, Srivastava G, Jolfaei A, et al. Security and Privacy in Shared HitLCPS Using a GA-Based Multiple-Threshold Sanitization Model. IEEE Transactions on Emerging Topics in Computational Intelligence. 2022, 6(1): 16-25. doi: 10.1109/tetci.2020.3032701
78. Abidi MH, Alkhalefah H, Umer U. Fuzzy harmony search based optimal control strategy for wireless cyber physical system with industry 4.0. Journal of Intelligent Manufacturing. 2021, 33(6): 1795-1812. doi: 10.1007/s10845-021-01757-4
79. Mohsin AH, Zaidan AA, Zaidan BB, et al. PSO–Blockchain-based image steganography: towards a new method to secure updating and sharing COVID-19 data in decentralised hospitals intelligence architecture. Multimedia Tools and Applications. 2021, 80(9): 14137-14161. doi: 10.1007/s11042-020-10284-y
80. Sathya Priya J, Saravanan K, Sathyabama AR. Optimized evolutionary algorithm and supervised ACO mechanism to mitigate attacks and improve performance of adhoc network. Computer Communications. 2020, 154: 551-558. doi: 10.1016/j.comcom.2020.02.070
81. Gupta M, Bhatt S, Alshehri AH, et al. Authorization Frameworks for Smart and Connected Ecosystems. Access Control Models and Architectures for IoT and Cyber Physical Systems. Published online 2022: 39-61. doi: 10.1007/978-3-030-81089-4_3
82. Althobaiti MM, Pradeep Mohan Kumar K, Gupta D, et al. An intelligent cognitive computing based intrusion detection for industrial cyber-physical systems. Measurement. 2021, 186: 110145. doi: 10.1016/j.measurement.2021.110145
83. Kannan C, Dakshinamoorthy M, Ramachandran M, et al. Cryptography‐based deep artificial structure for secure communication using IoT‐enabled cyber‐physical system. IET Communications. 2021, 15(6): 771-779. doi: 10.1049/cmu2.12119
84. Junejo AK, Komninos N. A Lightweight Attribute-Based Security Scheme for Fog-Enabled Cyber Physical Systems. Wireless Communications and Mobile Computing. 2020, 2020: 1-18. doi: 10.1155/2020/2145829
85. Xu Z, Liu X, Zhang G, et al. A Certificateless Signature Scheme for Mobile Wireless Cyber-Physical Systems. 2008 The 28th International Conference on Distributed Computing Systems Workshops. Published online June 2008. doi: 10.1109/icdcs.workshops.2008.84
86. Lima PM, Carvalho LK, Moreira MV. Ensuring confidentiality of cyber-physical systems using event-based cryptography. Information Sciences. 2023, 621: 119-135. doi: 10.1016/j.ins.2022.11.100
87. Abdi F, Chen CY, Hasan M, et al. Preserving Physical Safety Under Cyber Attacks. IEEE Internet of Things Journal. 2019, 6(4): 6285-6300. doi: 10.1109/jiot.2018.2889866
88. Romagnoli R, Krogh BH, de Niz D, et al. Software Rejuvenation for Safe Operation of Cyber–Physical Systems in the Presence of Run-Time Cyberattacks. IEEE Transactions on Control Systems Technology. 2023, 31(4): 1565-1580. doi: 10.1109/tcst.2023.3236470
89. Gu X, Easwaran A. Towards safe machine learning for CPS. Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems. Published online April 16, 2019. doi: 10.1145/3302509.3311038
90. Tyagi AK, Sreenath N. Cyber Physical Systems: Analyses, challenges and possible solutions. Internet of Things and Cyber-Physical Systems. 2021, 1: 22-33. doi: 10.1016/j.iotcps.2021.12.002
91. Shah A, Engineer M. A Survey of Lightweight Cryptographic Algorithms for IoT-Based Applications. Advances in Intelligent Systems and Computing. Published online November 20, 2018: 283-293. doi: 10.1007/978-981-13-2414-7_27
92. Jan MA, Khan F, Khan R, et al. Lightweight Mutual Authentication and Privacy-Preservation Scheme for Intelligent Wearable Devices in Industrial-CPS. IEEE Transactions on Industrial Informatics. 2021, 17(8): 5829-5839. doi: 10.1109/tii.2020.3043802
93. Lu Y, Wang D, Obaidat MS, et al. Edge-Assisted Intelligent Device Authentication in Cyber–Physical Systems. IEEE Internet of Things Journal. 2023, 10(4): 3057-3070. doi: 10.1109/jiot.2022.3151828
94. Laroui M, Nour B, Moungla H, et al. Edge and fog computing for IoT: A survey on current research activities & future directions. Computer Communications. 2021, 180: 210-231. doi: 10.1016/j.comcom.2021.09.003
95. Munoz DJ, Montenegro JA, Pinto M, et al. Energy-aware environments for the development of green applications for cyber–physical systems. Future Generation Computer Systems. 2019, 91: 536-554. doi: 10.1016/j.future.2018.09.006
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