A cyber-physical game framework for secure and resilient multi-agent autonomous systems

Zhiheng Xu, Quanyan Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The increasing integration of autonomous systems with publicly available networks exposes them to cyber attackers. An adversary can launch a man-in-the-middle attack to gain control of the system and inflict maximum damages with collision and suicidal attacks. To address this issue, this work establishes an integrative game and control framework to incorporate security into the automatic designs, and take into account the cyber-physical nature and the real-time requirements of the system. We establish a cyber-physical signaling game to develop an impact-aware cyber defense mechanism and leverage model-predictive control methods to design cyber-aware control strategies. The integrative framework enables the co-design of cyber-physical systems to minimize the inflicted systems, leading to online updating the cyber defense and physical layer control decisions. We use unmanned aerial vehicles (UAVs) to illustrate the algorithm, and corroborate the analytical results in two case studies.

Original languageEnglish (US)
Title of host publication54rd IEEE Conference on Decision and Control,CDC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5156-5161
Number of pages6
ISBN (Electronic)9781479978861
DOIs
StatePublished - Feb 8 2015
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: Dec 15 2015Dec 18 2015

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume54rd IEEE Conference on Decision and Control,CDC 2015
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other54th IEEE Conference on Decision and Control, CDC 2015
Country/TerritoryJapan
CityOsaka
Period12/15/1512/18/15

Keywords

  • Control systems
  • Games
  • Physical layer
  • Predictive control
  • Real-time systems
  • Receivers
  • Security

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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