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Response and Reconfiguration Under Attacks in CPS

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Encyclopedia of Cryptography, Security and Privacy
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Synonyms

Attack response; Reactive security; Resilient control systems

Definitions

A large amount of work in CPS security has focused on detecting attacks on real-time control systems; however, most of these attack detection studies do not discuss what to do after raising an alert. The aim of this entry is to summarize the design of real-time responses to operating control systems under attack.

Background

Before we talk about detecting and responding to attacks, we need to look at how control engineers have detected and responded to natural failures. Failures in the control equipment of physical infrastructures can cause irreparable harm to people, the environment, and other physical infrastructures. Therefore engineers have developed a variety of protections against accidents and natural causes, including safety systems, protection, fault detection, and robustness.

Safety

The basic principle recommended by the general safety standard for control systems (IEC 61508) is to obtain...

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References

  • Abdi F, Chen CY, Hasan M, Liu S, Mohan S, Caccamo M (2018) Guaranteed physical security with restart-based design for cyber-physical systems. In: Proceedings of the 9th ACM/IEEE international conference on cyber-physical systems. IEEE Press, pp 10–21

    Google Scholar 

  • Arroyo M, Kobayashi H, Sethumadhavan S, Yang J (2017) Fired: frequent inertial resets with diversification for emerging commodity cyber-physical systems. arXiv preprint arXiv:170206595

    Google Scholar 

  • Barreto C, Cárdenas AA, Quijano N (2013) Controllability of dynamical systems: threat models and reactive security. In: Decision and game theory for security. Springer, Cham, pp 45–64

    Chapter  MATH  Google Scholar 

  • Barth A, Rubinstein B, Sundararajan M, Mitchell J, Song D, Bartlett P (2012) A learning-based approach to reactive security. IEEE Trans Dependable Secure Comput 9(4):482–493. https://doi.org/10.1109/TDSC.2011.42

    Article  Google Scholar 

  • Cardenas AA, Amin S, Sastry S (2008) Secure control: towards survivable cyber-physical systems. In: 28th international conference on distributed computing systems workshops, 2008. ICDCS’08. IEEE, pp 495–500

    Google Scholar 

  • Cardenas AA, Amin S, Lin ZS, Huang YL, Huang CY, Sastry S (2011) Attacks against process control systems: risk assessment, detection, and response. In: Proceedings of the 6th ACM symposium on information, computer and communications security, pp 355–366

    Google Scholar 

  • Chen Y, Poskitt CM, Sun J (2018) Learning from mutants: using code mutation to learn and monitor invariants of a cyber-physical system. In: IEEE symposium on security and privacy

    Google Scholar 

  • Choi H, Lee WC, Aafer Y, Fei F, Tu Z, Zhang X, Xu D, Xinyan X (2018) Detecting attacks against robotic vehicles: a control invariant approach. In: Proceedings of the 2018 ACM SIGSAC conference on computer and communications security. ACM, pp 801–816

    Google Scholar 

  • Combita LF, Giraldo JA, Cardenas AA, Quijano N (2018) Dddas for attack detection and isolation of control systems. In: Handbook of dynamic data driven applications systems. Springer, Cham, pp 407–422

    Google Scholar 

  • Combita LF, Cardenas AA, Quijano N (2019) Mitigating sensor attacks against industrial control systems. IEEE Access 7:92444–92455

    Article  Google Scholar 

  • Farraj A, Hammad E, Daoud AA, Kundur D (2014) A game-theoretic control approach to mitigate cyber switching attacks in smart grid systems. In: Proceedings of the IEEE smart grid communications, Venice, pp 958–963

    Google Scholar 

  • Ganesan A, Rao J, Shin K (2017) Exploiting consistency among heterogeneous sensors for vehicle anomaly detection. Technical report, SAE Technical Paper

    Book  Google Scholar 

  • Giraldo J, Sarkar E, Cardenas AA, Maniatakos M, Kantarcioglu M (2017) Security and privacy in cyber-physical systems: a survey of surveys. IEEE Des Test 34:7–17

    Article  Google Scholar 

  • Giraldo J, Urbina D, Cardenas A, Valente J, Faisal M, Ruths J, Tippenhauer NO, Sandberg H, Candell R (2018) A survey of physics-based attack detection in cyber-physical systems. ACM Comput Surv (CSUR) 51(4):76

    Google Scholar 

  • Guo P, Kim H, Virani N, Xu J, Zhu M, Liu P (2017) Exploiting physical dynamics to detect actuator and sensor attacks in mobile robots. arXiv preprint arXiv:170801834

    Google Scholar 

  • Guo P, Kim H, Virani N, Xu J, Zhu M, Liu P (2018) Roboads: anomaly detection against sensor and actuator misbehaviors in mobile robots. In: 2018 48th annual IEEE/IFIP international conference on dependable systems and networks (DSN). IEEE, pp 574–585

    Google Scholar 

  • Hadžiosmanović D, Sommer R, Zambon E, Hartel PH (2014) Through the eye of the PLC: semantic security monitoring for industrial processes. In: Proceedings of the 30th annual computer security applications conference. ACM, pp 126–135

    Google Scholar 

  • He T, Zhang L, Kong F, Salekin A (2020) Exploring inherent sensor redundancy for automotive anomaly detection. In: 57th design automation conference

    Google Scholar 

  • Hu P, Li H, Fu H, Cansever D, Mohapatra P (2015) Dynamic defense strategy against advanced persistent threat with insiders. In: Proceedings of INFOCOM. To appear

    Book  Google Scholar 

  • Hwang I, Kim S, Kim Y, Seah CE (2009) A survey of fault detection, isolation, and reconfiguration methods. IEEE Trans Control Syst Technol 18(3):636–653

    Article  Google Scholar 

  • Kong F, Xu M, Weimer J, Sokolsky O, Lee I (2018) Cyber-physical system checkpointing and recovery. In: ACM/IEEE international conference on cyber-physical systems (ICCPS). ACM/IEEE

    Google Scholar 

  • Liu Y, Ning P, Reiter MK (2009) False data injection attacks against state estimation in electric power grids. In: Proceedings of the 16th ACM conference on computer and communications security. ACM, pp 21–32

    Google Scholar 

  • Ma R, Basumallik S, Eftekharnejad S, Fanxin K (2020) Recovery-based model predictive control for cascade mitigation under cyber-physical attacks. In: Texas power and energy conference (TPEC)

    Google Scholar 

  • McLaughlin S (2013) CPS: stateful policy enforcement for control system device usage. In: Proceedings of the 29th annual computer security applications conference, ACSAC’13. ACM, New York, pp 109–118

    Chapter  Google Scholar 

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

    Article  Google Scholar 

  • Müter M, Groll A, Freiling FC (2010) A structured approach to anomaly detection for in-vehicle networks. In: 2010 sixth international conference on information assurance and security. IEEE, pp 92–98

    Google Scholar 

  • Paridari K, O’Mahony N, Mady AED, Chabukswar R, Boubekeur M, Sandberg H (2018) A framework for attack-resilient industrial control systems: attack detection and controller reconfiguration. Proc IEEE 106(1):113–128

    Article  Google Scholar 

  • Piedrahita AFM, Gaur V, Giraldo J, Cardenas AA, Rueda SJ (2018) Virtual incident response functions in control systems. Comput Netw 135:147–159

    Article  Google Scholar 

  • Quinonez R, Giraldo J, Salazar L, Bauman E, Cardenas A, Lin Z (2020) SAVIOR: securing autonomous vehicles with robust physical invariants. In: 29th USENIX security symposium (USENIX Security 20)

    Google Scholar 

  • Sha L (2001) Using simplicity to control complexity. IEEE Softw 18(4):20–28. https://doi.org/10.1109/MS.2001.936213

    Article  Google Scholar 

  • Shelar D, Amin S (2015) Analyzing vulnerability of electricity distribution networks to der disruptions. In: American control conference (ACC), pp 2461–2468

    Google Scholar 

  • Summers AE (2003) Introduction to layers of protection analysis. J Hazard Mater 104(1–3):163–168

    Article  Google Scholar 

  • Taylor A, Leblanc S, Japkowicz N (2016) Anomaly detection in automobile control network data with long short-term memory networks. In: 2016 IEEE international conference on data science and advanced analytics (DSAA). IEEE, pp 130–139

    Google Scholar 

  • Urbina DI, Giraldo JA, Cardenas AA, Tippenhauer NO, Valente J, Faisal M, Ruths J, Candell R, Sandberg H (2016) Limiting the impact of stealthy attacks on industrial control systems. In: Proceedings of the 2016 ACM SIGSAC conference on computer and communications security. ACM, pp 1092–1105

    Google Scholar 

  • Yuan Y, Sun F, Liu H (2015) Resilient control of cyber-physical systems against intelligent attacker: a hierarchal stackelberg game approach. Int J Syst Sci. To appear

    MATH  Google Scholar 

  • Zhang L, Chen X, Kong F, Cardenas AA (2020) Real-time attack-recovery for cyber-physical systems using linear approximations. In: 2020 IEEE real-time systems symposium (RTSS). IEEE, pp 205–217

    Google Scholar 

  • Zhou K, Doyle JC (1998) Essentials of robust control, vol 104. Prentice Hall, Upper Saddle River

    MATH  Google Scholar 

  • Zhu Q, Basar T (2015) Game-theoretic methods for robustness, security, and resilience of cyberphysical control systems: games-in-games principle for optimal cross-layer resilient control systems. IEEE Control Syst 35(1):46–65

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Alvaro A. Cardenas .

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Cardenas, A.A. (2022). Response and Reconfiguration Under Attacks in CPS. In: Jajodia, S., Samarati, P., Yung, M. (eds) Encyclopedia of Cryptography, Security and Privacy. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27739-9_1729-1

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  • DOI: https://doi.org/10.1007/978-3-642-27739-9_1729-1

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  • Online ISBN: 978-3-642-27739-9

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