DoS Attacks on Remote State Estimation With Asymmetric Information

Ding, Kemi; Ren, Xiaoqiang; Quevedo, Daniel E.; Dey, Subhrakanti; Shi, Ling

doi:10.1109/tcns.2018.2867157

Cited by 61 publications

(17 citation statements)

References 23 publications

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“…Now, we are in the position to take the disturbance attenuation performance into consideration and derive a set of feasible sufficient conditions. (14)- (17) as well as the following constraints are satisfied:…”

Section: Resultsmentioning

confidence: 99%

“…To obtain the filter gains A f , B f , and E f to be designed in (4) and (5), we need to pay attention on seeking a group of available solutions, which yields the following theorem to implement some auxiliary mathematical tools. , , and , scalars , , > 1, and 0 < < 1, such that (16)- (17) as well as the following constraints are satisfied:…”

Section: Resultsmentioning

confidence: 99%

“…For example, to name a few, Li et al investigated the interactive decision‐making process by establishing a zero‐sum game and seeking the optimal Nash equilibrium for both sides . Then, Li et al built a Markov game by objective integration of estimation error covariance and communication costs and Ding et al generalized these results to multichannel case and took into account the impact of asymmetric information scheme . Besides, Zhang and Zheng addressed the linear quadratic control cost problem .…”

Section: Introductionmentioning

confidence: 99%

“…14 Then, Li et al built a Markov game by objective integration of estimation error covariance and communication costs 15 and Ding et al generalized these results to multichannel case 16 and took into account the impact of asymmetric information scheme. 17 Besides, Zhang and Zheng addressed the linear quadratic control cost problem. 18 However these descriptions of DoS attacks may be unreliable in some practical scenarios, as the packet losses caused by malicious adversaries need not obey a given class of probability distributions, which is drastically different from traditional networked control systems.…”

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confidence: 99%

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Resilient filtering for cyber‐physical systems under denial‐of‐service attacks

Shi

Wang

et al. 2019

Intl J Robust & Nonlinear

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Summary Owing to the deep integration of control, computation, and communication, cyber‐physical systems (CPSs) play an important role in wide real‐world applications. In this paper, we investigate the problem of resilient filter design of CPSs under malicious denial‐of‐service (DoS) attacks launched by adversaries. Firstly, based on two standard assumptions concerning with the frequency and duration of DoS attacks, we state the H∞ filtering problem for the CPSs under DoS attacks. Then, sufficient conditions are developed to ensure that, when there are DoS attacks, the filtering error dynamics of the underlying CPSs is mean square exponential stable with a prescribed H∞ disturbance attenuation performance. Furthermore, a switched filter is designed for CPSs under DoS attacks. Examples are given to illustrate the effectiveness and potential of the proposed new design techniques.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Resilient filtering for cyber‐physical systems under denial‐of‐service attacks

Shi

Wang

et al. 2019

Intl J Robust & Nonlinear

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“…. , L}, clearly, Ψ k−1 = −(AX k−1 +Ū k−1 )/η satisfies the condition in(17) for any η ≥ 3. Thus, by choosing the privacy-enhancing signals Γ…”

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confidence: 98%

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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Energy efficient management for distributed state estimation under DoS attacks

Lei

Yang

2021

Intl J Robust & Nonlinear

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In this article, we consider the issue of energy efficient management for distributed state estimation over unknown packet-dropping communication channels which are exposed to Denial-of-Service (DoS) attacks. After a packet is transmitted, the sensor determines whether to retransmit and the retransmission power levels based on the feedback information from the receiving sensor.We formulate the energy efficient management problem as a modified Markov decision problem (MMDP), and proposed an algorithm to seek a retransmission power schedule that achieves optimal tradeoff between energy consumption and communication rate for given channel noise power. In the case of unknown channel state, we design a statistical learning method to estimate channel noise power. Besides, inspired by the hypothesis testing, we design an anomaly detector to guarantee the instantaneity of channel noise power estimation and efficiency of energy management. Furthermore, we derive the optimal gain for each estimator, and provide a sufficient condition for the stability of estimator under the energy management. Finally, we verify the main results by numerical examples.

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DoS Attacks on Remote State Estimation With Asymmetric Information

Cited by 61 publications

References 23 publications

Resilient filtering for cyber‐physical systems under denial‐of‐service attacks

Resilient filtering for cyber‐physical systems under denial‐of‐service attacks

Learning-Based Attacks in Cyber-Physical Systems

Energy efficient management for distributed state estimation under DoS attacks

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