Design and Evaluation of Jamming Resilient Cyber-Physical Systems

Tomić, Ivana; Breza, Michael; Jackson, Gregory S.; Bhatia, Laksh; McCann, Julie A.

doi:10.1109/cybermatics_2018.2018.00138

Cited by 8 publications

(17 citation statements)

References 21 publications

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“…Adepu and Mathur [61] investigated single-point cyber-attacks against SWaT testbed and proposed attack detection based on system response to the attacks. Adepu et al [62] and Tomic et al [63] investigated jamming attacks against wireless communications in water systems. In [62], researchers carried out attacks against different parts of the SWaT testbed and, in [63], researchers used the Waterbox testbed [51] to investigate the robustness of process control schemes against jamming attacks using different attack strategies.…”

Section: Cyber-attack Modelsmentioning

confidence: 99%

A Systematic Review of the State of Cyber-Security in Water Systems

Tuptuk

Hazell

Watson

et al. 2021

Water

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Critical infrastructure systems are evolving from isolated bespoke systems to those that use general-purpose computing hosts, IoT sensors, edge computing, wireless networks and artificial intelligence. Although this move improves sensing and control capacity and gives better integration with business requirements, it also increases the scope for attack from malicious entities that intend to conduct industrial espionage and sabotage against these systems. In this paper, we review the state of the cyber-security research that is focused on improving the security of the water supply and wastewater collection and treatment systems that form part of the critical national infrastructure. We cover the publication statistics of the research in this area, the aspects of security being addressed, and future work required to achieve better cyber-security for water systems.

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Section: Cyber-attack Modelsmentioning

confidence: 99%

A Systematic Review of the State of Cyber-Security in Water Systems

Tuptuk

Hazell

Watson

et al. 2021

Water

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“…Dec , as a function of the duration L of the learning phase for three different control policies: I) unauthenticated control signalŪ k 1 = −aY k for all k, II) authenticated control signal (16), where Γ k are i.i.d. Gaussian N (0, 9), III) authenticated control signal (16), where Γ k are i.i.d. Gaussian N (0, 16).…”

Section: Privacy-enhancing Signalmentioning

confidence: 99%

“…Remark 9]. Here, we introduced the privacyenhancing signal (16) to impede the learning process of the attacker and decrease the deception probability. Another technique that has been developed in the literature to counter attacks, where the attacker has full system knowledge, is having the controller covertly introduce virtual state variables unknown to the attacker but that are correlated with the ordinary state variables, so that modification of the original states will impact the extraneous states.…”

Section: E Moving Target Defensementioning

confidence: 99%

Learning-Based Attacks in Cyber-Physical Systems

Khojasteh

Khina

Franceschetti

et al. 2021

IEEE Trans. Control Netw. Syst.

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We introduce the problem of learning-based attacks in a simple abstraction of cyber-physical systems-the case of a discrete-time, linear, time-invariant plant that may be subject to an attack that overrides the sensor readings and the controller actions. The attacker attempts to learn the dynamics of the plant and subsequently overrides the controller's actuation signal, to destroy the plant without being detected. The attacker can feed fictitious sensor readings to the controller using its estimate of the plant dynamics and mimic the legitimate plant operation. The controller, on the other hand, is constantly on the lookout for an attack; once the controller detects an attack, it immediately shuts the plant off. In the case of scalar plants, we derive an upper bound on the attacker's deception probability for any measurable control policy when the attacker uses an arbitrary learning algorithm to estimate the system dynamics. We then derive lower bounds for the attacker's deception probability for both scalar and vector plants by assuming an authentication test that inspects the empirical variance of the system disturbance. We also show how the controller can improve the security of the system by superimposing a carefully crafted privacy-enhancing signal on top of the "nominal control policy." Finally, for nonlinear scalar dynamics that belong to the Reproducing Kernel Hilbert Space (RKHS), we investigate the performance of attacks based on nonlinear Gaussian-processes (GP) learning algorithms.

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“…The performance of periodic and event-triggering networked control approaches under different types of jamming attacks was investigated in [ 58 ].…”

Section: An Overview Of Literature On Denial-of-service In Controlmentioning

confidence: 99%

“…We note that, among the different control approaches used for networked control systems under DoS attacks, event-triggered control (see, e.g., [ 25 , 38 , 48 , 54 , 58 ], and the references therein) appears to be the most commonly considered approach. We discuss the resiliency of event-triggering approaches against DoS attacks further in Section 5.1.1 .…”

Section: An Overview Of Literature On Denial-of-service In Controlmentioning

confidence: 99%

An Overview on Denial-of-Service Attacks in Control Systems: Attack Models and Security Analyses

Cetinkaya

Ishii

Hayakawa

2019

Entropy

136

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In this paper, we provide an overview of recent research efforts on networked control systems under denial-of-service attacks. Our goal is to discuss the utility of different attack modeling and analysis techniques proposed in the literature for addressing feedback control, state estimation, and multi-agent consensus problems in the face of jamming attacks in wireless channels and malicious packet drops in multi-hop networks. We discuss several modeling approaches that are employed for capturing the uncertainty in denial-of-service attack strategies. We give an outlook on deterministic constraint-based modeling ideas, game-theoretic and optimization-based techniques and probabilistic modeling approaches. A special emphasis is placed on tail-probability based failure models, which have been recently used for describing jamming attacks that affect signal to interference-plus-noise ratios of wireless channels as well as transmission failures on multi-hop networks due to packet-dropping attacks and non-malicious issues. We explain the use of attack models in the security analysis of networked systems. In addition to the modeling and analysis problems, a discussion is provided also on the recent developments concerning the design of attack-resilient control and communication protocols.

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Design and Evaluation of Jamming Resilient Cyber-Physical Systems

Cited by 8 publications

References 21 publications

A Systematic Review of the State of Cyber-Security in Water Systems

A Systematic Review of the State of Cyber-Security in Water Systems

Learning-Based Attacks in Cyber-Physical Systems

An Overview on Denial-of-Service Attacks in Control Systems: Attack Models and Security Analyses

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