Resilience Against Replay Attacks: A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems
In this paper, a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed. The methodological starting point relies on a smart use of predictive arguments with a twofold aim: 1) Promptly detect malicious agent be...
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| Published in | IEEE/CAA journal of automatica sinica Vol. 8; no. 3; pp. 628 - 640 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Piscataway
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
01.03.2021
DIMES Department, University of Calabria, Arcavacata di Rende 87036, Italy |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2329-9266 2329-9274 |
| DOI | 10.1109/JAS.2020.1003542 |
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| Abstract | In this paper, a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed. The methodological starting point relies on a smart use of predictive arguments with a twofold aim: 1) Promptly detect malicious agent behaviors affecting normal system operations; 2) Apply specific control actions, based on predictive ideas, for mitigating as much as possible undesirable domino effects resulting from adversary operations. Specifically, the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent. Finally, numerical simulations are carried out to show benefits and effectiveness of the proposed approach. |
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| AbstractList | In this paper, a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed. The methodological starting point relies on a smart use of predictive arguments with a twofold aim: 1) Promptly detect malicious agent behaviors affecting normal system operations; 2) Apply specific control actions, based on predictive ideas, for mitigating as much as possible undesirable domino effects resulting from adversary operations. Specifically, the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent. Finally, numerical simulations are carried out to show benefits and effectiveness of the proposed approach. |
| Author | Famularo, Domenico Tedesco, Francesco Franze, Giuseppe |
| AuthorAffiliation | DIMES Department, University of Calabria, Arcavacata di Rende 87036, Italy |
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| SubjectTerms | Algorithms Cyberattack Distributed model predictive control Graph theory leader-follower networks Mathematical models Multi-agent systems Multiagent systems Predictive control replay attacks Resilience resilient control Security Topology Trajectory |
| Title | Resilience Against Replay Attacks: A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems |
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