Resilient Control for Cyber-Physical Systems Subject to Replay Attacks

Franzè, Giuseppe; Tedesco, Francesco; Lúcia, Walter

doi:10.1109/lcsys.2019.2920507

Cited by 65 publications

(24 citation statements)

References 8 publications

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“…9 For linear systems, MPC designs have been explored that can guarantee exponential stability of the origin in the presence of sufficiently short denial of service attacks, 10 guarantee boundedness of the closed-loop state in an invariant set under random cyberattacks on the sensor measurements, 11 and handle replay attacks. 12 For nonlinear systems, Chen et al 13 combined a neural network-based attack detection technique developed in 3 with a two-layer control architecture, where the upper layer is a Lyapunov-based MPC, to guarantee closed-loop stability after attacks are detected. Durand 14 explored several MPC techniques with economics-based objective functions (known as economic MPC's [EMPC's] 15,16 ) in the presence of false sensor measurements to explore cyberattacks in a nonlinear systems context.…”

Section: Introductionmentioning

confidence: 99%

Integrated cyberattack detection and resilient control strategies using Lyapunov‐based economic model predictive control

Oyama

Durand

2020

AIChE Journal

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The use of an integrated system framework, characterized by numerous cyber/physical components (sensor measurements, signals to actuators) connected through wired/wireless networks, has not only increased the ability to control industrial systems but also the vulnerabilities to cyberattacks. State measurement cyberattacks could pose threats to process control systems since feedback control may be lost if the attack policy is not thwarted. Motivated by this, we propose three detection concepts based on Lyapunov-based economic model predictive control (LEMPC) for nonlinear systems. The first approach utilizes randomized modifications to an LEMPC formulation online to potentially detect cyberattacks. The second method detects attacks when a threshold on the difference between state measurements and state predictions is exceeded. Finally, the third strategy utilizes redundant state estimators to flag deviations from "normal" process behavior as cyberattacks.

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Section: Introductionmentioning

confidence: 99%

Integrated cyberattack detection and resilient control strategies using Lyapunov‐based economic model predictive control

Oyama

Durand

2020

AIChE Journal

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“…where ξ (k) also satisfies Assumption 1. Then the following theorem is given to show the boundary and stabilization properties of systems (31). Theorem 3: Consider the interactive CVSs subject to cyber-attacks in the overall systems (31).…”

Section: Robustness Analysis With Cyber-attacks In the Overall Sysmentioning

confidence: 99%

“…Then the following theorem is given to show the boundary and stabilization properties of systems (31). Theorem 3: Consider the interactive CVSs subject to cyber-attacks in the overall systems (31). The systems are bounded for any injection ξ and ξ satisfying (7) if the conditions (i), (iii) and (iv) in Lemma 3 hold and σ( √ 2D) ⊂ B(0, 1).…”

Section: Robustness Analysis With Cyber-attacks In the Overall Sysmentioning

confidence: 99%

“…In this section, we assume that the virtual system (hidden network) is also attacked as described in (31), where ξ i (k) is considered to have the same limitation as ξ i (k) in IV-C, and the hidden network used is identical with it in IV-D. As shown in Fig. 6, the stability of the vehicle platoon is still guaranteed despite of the attacks on both networks.…”

Section: E the Case Against Cyber-attacks In The Vehicle Platoon Laymentioning

confidence: 99%

“…Replay attacks intercept system data and maliciously retransmit, destroying system functionality [30]- [33]. Distributed receding-horizon control approach [30], [31] and recursive distributed Kalman fusion estimator (DKFE) [32] are effective strategies to ensure the consensus of CPS under replay attacks. Deception attacks, including data modification, data replay, and false data injection, modify messages transmitted between agents and may undermine the integrity of CPS [34]- [37].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Resilient Control Design of the Third-Order Discrete-Time Connected Vehicle Systems Against Cyber-Attacks

Liu

2020

IEEE Access

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This paper investigates the consensus problems of the third-order discrete-time Connected Vehicle Systems (CVSs) under cyber-attacks. First, the necessary and sufficient conditions for consensus of third-order discrete-time CVSs are derived in the absence of attacks by using algebraic graph and matrix theory. Then the interaction network framework between the original CVSs in the vehicle platoon layer and a virtual system in the hidden layer is established to resist cyber-attacks. Since sufficiently large attacks can be excluded from CVSs through a threshold defense mechanism, such potential attacks considered are bounded and generated by any linear or non-linear finite L2-gain exogenous dynamics system. It is proved that the stability of CVSs can be ensured and the state errors converge to a bounded range whether the attacks exist only in the vehicle platoon layer or in the overall systems (including the vehicle platoon layer and the hidden layer) by using the Lyapunov stability method. Finally, a simulation example containing several scenarios demonstrates the effectiveness and superiority of the proposed methods.

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Resilient control of cyber‐physical systems using adaptive super‐twisting observer

Nateghi

Shtessel

Edwards

et al. 2022

Asian Journal of Control

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In this work, the problem of online secure state estimation and attack reconstruction in the face of offensives that corrupt the sensor measurements and modify the actuator commands of cyber–physical systems is investigated for designing a resilient controller for the system. The states of cyber–physical system and its actuator attacks are estimated/reconstructed online using a novel adaptive line‐by‐line super‐twisting observer, whereas sparse stealth attacks on unprotected sensors are reconstructed using a sparse recovery algorithm. The estimated attacks are used for attack compensation by a resilient controller. The efficacy of the proposed technique is illustrated via simulation on a real electric power system under deception actuator attack and stealth sensor attack.

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Resilient Control for Cyber-Physical Systems Subject to Replay Attacks

Cited by 65 publications

References 8 publications

Integrated cyberattack detection and resilient control strategies using Lyapunov‐based economic model predictive control

Integrated cyberattack detection and resilient control strategies using Lyapunov‐based economic model predictive control

Resilient Control Design of the Third-Order Discrete-Time Connected Vehicle Systems Against Cyber-Attacks

Resilient control of cyber‐physical systems using adaptive super‐twisting observer

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