Data-Importance-Aware Attack Strategy Design and Secure Control Countermeasure

This paper is concerned with the security issues related to integrated attack-defense strategy for a category of multi-sensor networked control systems with state saturation constraints. In general, existing denial-of-service (DoS) attack models typically conduct indiscriminate attacks on data packets, disregarding the significance of the attacked data packets to the system. Note that the measurement data from different sensor nodes possesses varying levels of importance. In light of this, we first propose a novel form of attack from the perspective of attack design, known as a data-importance-aware attack. The importance of data refers to the quantitative impact of the measured values at each sensor node on the stable and safe operation of the entire system. As such, the proposed attack has the awareness to launch attacks against critical sensor nodes, rendering data unable to be transmitted. Then, an attack-node-dependent security controller is devised from the defender’s perspective against the constructed attack, which can effectively resist the impact of attacks and stabilize the system. By employing the Lyapunov functional method, sufficient conditions are derived to ensure the asymptotic stability of the closed-loop system. Finally, the reliability and effectiveness of the node importance-aware attack strategy and control countermeasure are validated by numerical simulation.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Information Forensics and Security
Published
2024-12-25
DOI
https://doi.org/10.1109/tifs.2024.3522770
Citations
6
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
2.09

Funders

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article

Data-Importance-Aware Attack Strategy Design and Secure Control Countermeasure

Jiancun Wu, Engang Tian, Zhiru Cao, Chen Peng
6 citations
IEEE Transactions on Information Forensics and Security
Network Security and Intrusion Detection
2.09
article

Data-Importance-Aware Attack Strategy Design and Secure Control Countermeasure

Jiancun Wu, Engang Tian, Zhiru Cao, Chen Peng
article en
6 citations

Abstract

This paper is concerned with the security issues related to integrated attack-defense strategy for a category of multi-sensor networked control systems with state saturation constraints. In general, existing denial-of-service (DoS) attack models typically conduct indiscriminate attacks on data packets, disregarding the significance of the attacked data packets to the system. Note that the measurement data from different sensor nodes possesses varying levels of importance. In light of this, we first propose a novel form of attack from the perspective of attack design, known as a data-importance-aware attack. The importance of data refers to the quantitative impact of the measured values at each sensor node on the stable and safe operation of the entire system. As such, the proposed attack has the awareness to launch attacks against critical sensor nodes, rendering data unable to be transmitted. Then, an attack-node-dependent security controller is devised from the defender’s perspective against the constructed attack, which can effectively resist the impact of attacks and stabilize the system. By employing the Lyapunov functional method, sufficient conditions are derived to ensure the asymptotic stability of the closed-loop system. Finally, the reliability and effectiveness of the node importance-aware attack strategy and control countermeasure are validated by numerical simulation.

IEEE Transactions on Information Forensics and SecurityVol. 20
Shanghai University (CN), University of Shanghai for Science and Technology (CN)
Natural Science Foundation of Shanghai, National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 11%
Network Security and Intrusion Detection
2.09
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Data-Importance-Aware Attack Strategy Design and Secure Control Countermeasure — Jiancun Wu, Engang Tian, et al. · IEEE Transactions on Information Forensics and Security (2024) | TGRS Research Map | TGRS