Dynamic distributed intrusion detection for secure multi-robot systems

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.

[1]  Richard Bellman,et al.  Introduction to the mathematical theory of control processes , 1967 .

[2]  Pieter Collins,et al.  Continuity and computability of reachable sets , 2005, Theor. Comput. Sci..

[3]  Richard H. Baker,et al.  The computer security handbook , 1985 .

[4]  Magnus Egerstedt,et al.  Observability of Switched Linear Systems , 2004, HSCC.

[5]  John N. Tsitsiklis,et al.  A survey of some aspects of parallel and distributed iterative algorithms , 1989 .

[6]  G. Dini,et al.  Tolerating, Malicious Monitors in Detecting Misbehaving Robots , 2008, 2008 IEEE International Workshop on Safety, Security and Rescue Robotics.

[7]  Charles P. Pfleeger,et al.  Security in computing , 1988 .

[8]  George J. Pappas,et al.  Observability of Switched Linear Systems in Continuous Time , 2005, HSCC.

[9]  Antonio Bicchi,et al.  Decentralized intrusion detection for secure cooperative multi-agent systems , 2007, 2007 46th IEEE Conference on Decision and Control.

[10]  Sampath Kannan,et al.  Polyhedral Flows in Hybrid Automata , 1999, HSCC.

[11]  Antoine Girard,et al.  Reachability Analysis of Nonlinear Systems Using Conservative Approximation , 2003, HSCC.

[12]  Magnus Egerstedt,et al.  Observability and estimation in distributed sensor networks , 2007, 2007 46th IEEE Conference on Decision and Control.

[13]  S. Shankar Sastry,et al.  Observability of Linear Hybrid Systems , 2003, HSCC.

[14]  Oded Maler,et al.  Reachability Analysis via Face Lifting , 1998, HSCC.

[15]  Antonio Bicchi,et al.  Distributed intrusion detection for secure consensus computations , 2007, 2007 46th IEEE Conference on Decision and Control.

[16]  Antoine Girard,et al.  Zonotope/Hyperplane Intersection for Hybrid Systems Reachability Analysis , 2008, HSCC.

[17]  Antonio Bicchi,et al.  Consensus-based distributed intrusion detection for multi-robot systems , 2008, 2008 IEEE International Conference on Robotics and Automation.

[18]  M. Egerstedt,et al.  Motion probes for fault detection and recovery in networked control systems , 2008, 2008 American Control Conference.

[19]  John N. Tsitsiklis,et al.  Distributed Asynchronous Deterministic and Stochastic Gradient Optimization Algorithms , 1984, 1984 American Control Conference.

[20]  Antonio Bicchi,et al.  Local Monitor Implementation for Decentralized Intrusion Detection in Secure Multi-Agent Systems , 2007, 2007 IEEE International Conference on Automation Science and Engineering.

[21]  Antoine Girard,et al.  Reachability of Uncertain Linear Systems Using Zonotopes , 2005, HSCC.

[22]  Azim Eskandarian,et al.  The threat of intelligent collisions , 2004, IT Professional.

[23]  Davide Bresolin,et al.  Reachability computation for hybrid systems with Ariadne , 2008 .

[24]  Richard M. Murray,et al.  Complexity Management in the State Estimation of Multi‐Agent Systems , 2007 .

[25]  D. Wishart.  Introduction to the Mathematical Theory of Control Processes. Volume 1—Linear Equations and Quadratic Criteria , 1969 .

[26]  Zdzisław Denkowski,et al.  Set-Valued Analysis , 2021 .