Detection of Cyber Attacks on Leader-Following Multi-Agent Systems

This paper studies an attack detection problem for a networked leader-following multi-agent system subject to unknown-but-bounded system noises and quantization effects, where an adversary launches malicious cyber attacks on agents' measurement outputs aiming to distrust the leader-following co...

Full description

Saved in:
Bibliographic Details
Published in:IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society Vol. 1; pp. 6243 - 6248
Main Authors: Mousavinejad, Eman, Ge, Xiaohua, Han, Qing-Long, Yang, Fuwen, Vlacic, Ljubo
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2019
Subjects:
Cyber attack detection
Cyberattack
Ellipsoids
Filtering
leader-following consensus
multi-agent systems (MASs)
Noise measurement
Protocols
quantization
Quantization (signal)
set-membership filtering
State estimation
ISSN:2577-1647
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper studies an attack detection problem for a networked leader-following multi-agent system subject to unknown-but-bounded system noises and quantization effects, where an adversary launches malicious cyber attacks on agents' measurement outputs aiming to distrust the leader-following consensus. An effective distributed attack detection algorithm is firstly developed for each follower such that the attack can be identified at the time of its occurrence. The core of the algorithm lies in a set-membership filtering approach from which each designed filter can provide an ellipsoidal state prediction set and an ellipsoidal state estimation set. Whether a filter can detect the occurrence of such an attack is then determined by the existence of intersection between these two sets. Furthermore, a convex optimization algorithm is established to solve out anticipated consensus protocol and two-step set-membership filter by resorting to some recursive linear matrix inequalities. Finally, an illustrative example is given to show the effectiveness of the proposed main results.
ISSN:2577-1647
DOI:10.1109/IECON.2019.8927195