Secure Event-Triggered Distributed Kalman Filters for State Estimation Over Wireless Sensor Networks

Mustafa, Aquib; Mazouchi, Majid; Modares, Hamidreza

doi:10.1109/tsmc.2022.3195121

Cited by 16 publications

(3 citation statements)

References 47 publications

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“…Remark 8: On the basis of the induction, recursive method, and stochastic matrix theory, certain UBs have been established in Theorem 1 to suppress the actual EVs. Furthermore, the gain parameter has been devised in Theorem 2, under which the solutions to the coupled difference equations ( 12) and (24) provide the locally minimal bounds on the EVs. It is observed that the expressions of the minimal UBs developed in the main results embrace all the information about the system parameters, the noise constraints, the scheduling of the data transmission, and the variation range of the gain perturbation.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, an illustrated example has been presented to show usefulness of the robust filtering strategy. Further research directions would include some potential extensions of the main results to more complicated systems under communication constraints, such as 2-D nonlinear systems under codingdecoding mechanisms and eavesdropping attacks [24], [28].…”

Section: Discussionmentioning

confidence: 99%

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Robust Filtering for 2-D Systems With Uncertain-Variance Noises and Weighted Try-Once-Discard Protocols

Wang

Liang

Lam

et al. 2023

IEEE Trans. Syst. Man Cybern, Syst.

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The robust filtering problem is tackled for a class of shift-varying 2-D systems with uncertain-variance noises under the scheduling of weighted try-once-discard (WTOD) protocol. The measurements collected from the sensors are transmitted to a remote filter via a shared network. To alleviate the communication burden and obviate the network congestion, the WTOD protocol is adopted to orchestrate the data transmission, where a sensor node is solely permitted to broadcast its information to the remote filter at every transmission step. Moreover, the resilient filter is exploited to regulate the possible gain perturbation. The objective of the addressed problem is to design a robust filter in a recursive structure such that, in the simultaneous presence of the uncertain-variance noises and the WTOD protocol, the minimal upper bounds (UBs) on the filtering error variances (EVs) are developed for the considered system. First, by means of induction and stochastic analysis technique, certain UBs in terms of coupled recursive difference equations are derived for the actual EVs. Then, a proper filter is carefully designed which achieves the minimization of the obtained UBs at each step. Finally, an illustrative example is presented to verify the usefulness of the proposed protocol-based filtering method.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Robust Filtering for 2-D Systems With Uncertain-Variance Noises and Weighted Try-Once-Discard Protocols

Wang

Liang

Lam

et al. 2023

IEEE Trans. Syst. Man Cybern, Syst.

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“…In [10], A distributed attack detection mechanism is devised for deception attacks on communication links in sensor networks. In [23], meta-Bayes combined with an attack detection mechanism are used to reduce the impact of attacks. A protection scheme is proposed in [24] to keep the information communication channel of the system from FDI attacks.…”

Section: Introductionmentioning

confidence: 99%

Trust-Based Distributed H_∞ Diffusion Filtering for Target Tracking Under Cyber Attacks

Gao,

Zhu,

et al. 2023

IEEE Access

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Concerning the problem of target tracking in wireless sensor networks under cyber attacks, this paper proposes a trust-based distributed H  diffusion filtering method, designed to maintain resilience against diverse types of cyber attacks. Firstly, the distributed H  filtering equation for a linear discrete system is implemented for iterative updates of state estimation and error covariance. Secondly, to address the impact of cyber attacks, the K-means-based trust set extracting algorithm is employed to identify and remove attacked untrusted nodes. Subsequently, the data from trusted nodes is fused based on a diffusion strategy, leading to recalculations of state estimation and covariance, thus improving the overall target tracking performance. Experimental results demonstrate the effectiveness of our method in resisting denial of service attacks and deception attacks, such as random, replay, and false data injection attacks. The proposed approach offers robustness and adaptability, making it suitable for practical applications in distributed sensor networks under cyber attacks.INDEX TERMS Cyber attacks, distributed H  diffusion filtering, wireless sensor network, target tracking.

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A Periodic Dynamic Encoding Mechanism for Stealthy Attack Detection in Distributed State Estimation

Ding,

Yang,

Liu

et al. 2024

Intl J Robust & Nonlinear

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This article deals with the design and defense issues of false data injection attack in distributed state estimation. At each time step, each sensor sends its estimate to neighboring sensors. To verify the security of the received data, a column vector composed of state estimate differences is used as the detection variable. Based on the data directly obtained by the attacker in the wireless communication network, an attack strategy is established to degrade the system estimation performance while not being detected by the detector. Under the attack strategy, the update of the estimation error covariance is analyzed and the optimal attack parameters are obtained. To enhance the security of the system, a periodic dynamic encoding mechanism is proposed to prevent attackers from eavesdropping on original data, which consists of two stages: preparation stage and periodic encoding stage. It is proved that the proposed encoding mechanism can destroy the stealthiness of the attack, thus ensuring the detection ability of the detector. Numerical simulations are given to verify the results of the theoretical analysis.

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Secure Event-Triggered Distributed Kalman Filters for State Estimation Over Wireless Sensor Networks

Cited by 16 publications

References 47 publications

Robust Filtering for 2-D Systems With Uncertain-Variance Noises and Weighted Try-Once-Discard Protocols

Robust Filtering for 2-D Systems With Uncertain-Variance Noises and Weighted Try-Once-Discard Protocols

Trust-Based Distributed H_∞ Diffusion Filtering for Target Tracking Under Cyber Attacks

A Periodic Dynamic Encoding Mechanism for Stealthy Attack Detection in Distributed State Estimation

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Secure Event-Triggered Distributed Kalman Filters for State Estimation Over Wireless Sensor Networks

Cited by 16 publications

References 47 publications

Robust Filtering for 2-D Systems With Uncertain-Variance Noises and Weighted Try-Once-Discard Protocols

Robust Filtering for 2-D Systems With Uncertain-Variance Noises and Weighted Try-Once-Discard Protocols

Trust-Based Distributed H∞ Diffusion Filtering for Target Tracking Under Cyber Attacks

A Periodic Dynamic Encoding Mechanism for Stealthy Attack Detection in Distributed State Estimation

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Product

Resources

About

Trust-Based Distributed H_∞ Diffusion Filtering for Target Tracking Under Cyber Attacks