A general technique to build a dynamic and distributed intrusion detector for a class of multi–agent systems is proposed in this paper, by which misbehavior in the motion of one or more agents can be discovered. Previous work from the authors has focused on how to distinguish the behavior of a misbehaving agent in a completely distributed way, by developing a solution where agents act as local monitors of their neighbors and use locally sensed information as well as data received from other monitors at a particular time. In this work, we improve the system detection capability by allowing monitors to use information collected at different instants and thus realizing a dynamic state observer that is valid for any system in the considered class. Finally, we show through simulations the effectiveness of the proposed solution for a case study.
Fagiolini, A., Babboni, F., Bicchi, A. (2009). Dynamic Distributed Intrusion Detection for Secure Multi–Robot Systems. In Proceedings of IEEE International Conference on Robotics and Automation (pp. 2723-2728) [10.1109/ROBOT.2009.5152608].
Dynamic Distributed Intrusion Detection for Secure Multi–Robot Systems
FAGIOLINI, Adriano;
2009-01-01
Abstract
A general technique to build a dynamic and distributed intrusion detector for a class of multi–agent systems is proposed in this paper, by which misbehavior in the motion of one or more agents can be discovered. Previous work from the authors has focused on how to distinguish the behavior of a misbehaving agent in a completely distributed way, by developing a solution where agents act as local monitors of their neighbors and use locally sensed information as well as data received from other monitors at a particular time. In this work, we improve the system detection capability by allowing monitors to use information collected at different instants and thus realizing a dynamic state observer that is valid for any system in the considered class. Finally, we show through simulations the effectiveness of the proposed solution for a case study.File | Dimensione | Formato | |
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