4.7 Article

Detection of Nonrandom Sign-Based Behavior for Resilient Coordination of Robotic Swarms

期刊

IEEE TRANSACTIONS ON ROBOTICS
卷 38, 期 1, 页码 92-109

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2021.3139592

关键词

Robots; Robot sensing systems; Robot kinematics; Multi-robot systems; Monitoring; Task analysis; Cyberattack; Attack detection; distributed robot systems; multirobot systems; swarms

类别

资金

  1. National Science Foundation [1816591]
  2. Office of Naval Research [N000141712012]
  3. U.S. Department of Defense (DOD) [N000141712012] Funding Source: U.S. Department of Defense (DOD)
  4. Direct For Computer & Info Scie & Enginr
  5. Division Of Computer and Network Systems [1816591] Funding Source: National Science Foundation

向作者/读者索取更多资源

This study proposes a runtime monitoring framework that detects and isolates hidden attacks within a multirobot system by monitoring changes in the signed residual. It triggers alarms when an attack is discovered.
Cooperative multirobot systems coordinate their motion by exchanging information through consensus schemes to achieve a common goal. In the event of stealthy cyber attacks, compromised measurements and communication broadcasts can hijack a portion or the entire system toward undesired states. However, in order for these attacks to be effective, they have to exhibit nonrandom characteristics that contradict the expected multirobot system behavior. To deal with these hidden attacks, we propose a runtime monitoring framework that considers the signed residual, defined as the difference between the expected and the received information to identify and isolate unexpected nonrandom behavior within the multirobot system. Specifically, the technique that we propose-named Cumulative Sign detector-monitors and compares changes in signed values of residual with their expected occurrences to detect inconsistencies and trigger alarms when an attack is discovered. Our results are validated theoretically by providing detection bounds and are demonstrated with simulations and experiments on swarms of unmanned ground vehicles under different attacks in comparison with state-of-the-art residual-based detection schemes.

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