Finite energy and bounded actuator attacks on cyber-physical systems

Djouadi, Seddik M.; Melin, Alexander M.; Ferragut, Erik M.; Laska, Jason A.; Dong, Jin; Drira, Anis

doi:10.1109/ecc.2015.7331099

Cited by 15 publications

(17 citation statements)

References 8 publications

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“…If the actuator attack signal is constant, then there exists a finite-time T ′ such that . d f (t) = 0, t ≥ T ′ , and consequently, by (26), V(e(t),d f (t)) < 0, t ≥ T ′ , for ||e(t)|| 2 > 2||P|| 2 ||B 1 || 2 min (Q) || n−d+1 (t)|| 2 , t ≥ T ′ . Therefore, it follows from theorem 4.15 in the work of Haddad and Chellaboina 30 that the system given by (25) is input-to-state stable with respect to n − d + 1 (t).…”

Section: Adaptive Corrective Control Signalmentioning

confidence: 93%

“…4,11,17,18,22,26,27 Consequently, as shown in Figure 1, it is assumed that the control inputũ(t) is compromised so that Here, a false data injection actuator attack is considered, where an attacker modifies the data sent from the controller to the actuators.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Theorem 1 shows that the bound given by (21) can be made arbitrary small if is chosen sufficiently large. d f (t) = 0, t ≥ T ′ , and consequently, by (26), This can be remedied by adding a modification term in the update laws to filter out high frequency content in the control signal while preserving system stability.…”

Section: Adaptive Corrective Control Signalmentioning

confidence: 99%

“…The attacker's goal is to prevent the actuator from receiving correct data and control packets, thereby injecting false information to the actuators. 4,11,17,18,22,26,27 Consequently, as shown in Figure 1, it is assumed that the control inputũ(t) is compromised so that…”

Section: Problem Formulationmentioning

confidence: 99%

“…In the presence of an outlier the feedback loop is then closed using an estimated value of the sensor measurements. Recently, mitigating the effects of sensor uncertainties in networked multiagent systems is considered in the works of Ding et al 24 and Arabi et al 25 In this paper, an output-feedback adaptive control architecture is presented to suppress or counteract the effect of false data injection actuator attacks 4,11,17,18,22,26,27 in linear systems, where it is assumed that the attacker is capable of maliciously manipulating the controller commands to the actuators. In particular, the proposed controller is composed of two components, namely, a nominal controller and an additive corrective signal.…”

mentioning

confidence: 99%

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An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

Yadegar

Meskin

Haddad

2019

Adaptive Control & Signal

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In this paper, we present a control design framework wherein an adaptive-based corrective signal is augmented to the output of the nominal controller in order to suppress or counteract the effect of malicious actuator attacks. Due to the unavailability of full-state measurements, a nonminimal controllable realization of the nominal closed-loop system is used to design the corrective signal predicated on partial state information. Two illustrative numerical examples are given to demonstrate the efficacy of the proposed adaptive control architecture. KEYWORDSactuator attacks, adaptive control, cyber-physical systems, output feedback INTRODUCTIONCyber-physical systems (CPSs) have different meanings to different researchers and practitioners. The common thread in CPSs is the fact that they involve the integration of computation, communication, and physics working together in order to achieve required control objectives. These systems usually consist of networked agents, which include actuators, sensors, communication devices, and control processing units. 1 Since communication and computation devices are becoming cheaper and smaller, they are extensively used to interact directly with the physical environment, and hence, the use of these devices is becoming ubiquitous. Therefore, sensors and actuators, which collect, exchange, and use data in a CPS, are designed such that they can be interfaced with network and communication devices. The main reason of the advent of CPSs is the tight integration of the physical processes they control and computational resources and communication capabilities that exist in modern engineering systems. 2 The CPS architectures are being used in many different applications such as power systems, transportation systems, process control systems, large-scale manufacturing systems, ecological systems, and health care systems. Many of these applications involve safety-critical systems, and hence, any failures or cyber-attacks can cause catastrophic damage to the physical system being controlled resulting in drastic societal ramifications.Due to the open communication and computation platform architectures of CPS, one of the most important challenges in these systems is their vulnerability to malicious cyber-attacks. Cyber-attacks can severely compromise system stability, performance, and integrity. In particular, malicious attacks in feedback control systems can compromise sensor measurements as well as actuator commands to severely degrade closed-loop system performance and integrity. Cyber-attacks are continuously becoming more sophisticated and intelligent, and hence, it is vital to develop algorithms that can suppress their effects on CPSs. 3 Depending on the a priori system knowledge and the available resources of the attacker, different malicious attacks can be injected into CPSs. 4 The available resources of the attacker can be generally categorized as disclosure and disruption Int J Adapt Control Signal Process. 2019;33:943-955.wileyonlinelibrary.com/journal/acs

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Section: Adaptive Corrective Control Signalmentioning

confidence: 93%

Section: Problem Formulationmentioning

confidence: 99%

Section: Adaptive Corrective Control Signalmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

mentioning

confidence: 99%

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An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

Yadegar

Meskin

Haddad

2019

Adaptive Control & Signal

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Hamiltonian‐driven adaptive dynamic programming for mixedH₂/H_∞performance using sum‐of‐squares

Yang

Mazouchi

Modares

2021

Intl J Robust & Nonlinear

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In this article, the mixed H2/H∞ performance optimization is first formulated as a nonzero‐sum game, of which the sufficient condition guaranteeing the existence of the Nash equilibrium is derived using the Hamilton–Jacobi (HJ) theory. Then, Hamiltonian‐driven inequalities are presented to evaluate the H2 and H∞ performances. Using this Hamiltonian‐inequality driven approach, the coupled HJ equations arising from finding the Nash equilibrium are relaxed to the HJ inequality constraints. A novel mixed policy iteration (PI) algorithm is developed that uses sum‐of‐squares (SOS) program in policy evaluation step, and consists of an H2 performance improvement step and an H∞ performance guarantee step. This constrained‐driven approach allows us to present a PI algorithm that takes into account both robustness and performance objectives. Finally, a numerical simulation is carried out to highlight the efficacy of the proposed framework.

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Cyber-Physical Robustness Assessment of Stormwater Controls with Real-Time Mechanism for Smart and Sustainable Urban Water Resources Management

Bathi

Ellis

Liang

et al. 2022

World Environmental and Water Resources Congress 2022

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Finite energy and bounded actuator attacks on cyber-physical systems

Cited by 15 publications

References 8 publications

An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

Hamiltonian‐driven adaptive dynamic programming for mixedH₂/H_∞performance using sum‐of‐squares

Cyber-Physical Robustness Assessment of Stormwater Controls with Real-Time Mechanism for Smart and Sustainable Urban Water Resources Management

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Finite energy and bounded actuator attacks on cyber-physical systems

Cited by 15 publications

References 8 publications

An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

Hamiltonian‐driven adaptive dynamic programming for mixedH2/H∞performance using sum‐of‐squares

Cyber-Physical Robustness Assessment of Stormwater Controls with Real-Time Mechanism for Smart and Sustainable Urban Water Resources Management

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Hamiltonian‐driven adaptive dynamic programming for mixedH₂/H_∞performance using sum‐of‐squares