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Cybersecurity and Safety Challenges in Autonomous Vehicles: Threats Identification and Countermeasures Development

NCJ Number
310590
Author(s)
Sangjun Lee; Byung-Cheol Min
Date Published
October 2018
Length
9 pages
Abstract
This study proposes a Direction of Arrival (DoA)-aided attack detection scheme to identify cyberattacks on networked multi-robot systems. For each agent, a local estimator is designed to generate robust residuals, and a parametric statistical tool corresponding to the residuals is elaborated to build sensitive decision rules. These locally stored residuals and thresholds are shared between robots via a wireless network, allowing a multi-robot system to complete its mission in the presence of one or more compromised agents. The proposed DoA-aided attack detection scheme is tested on a multi-robot testbed with a team of 10 robots. Experimental results demonstrate that the proposed detection scheme enables each robot to identify malicious activities without shearing the global coordination. (Publisher abstract provided.)