TY - GEN
T1 - Targeted attacks on teleoperated surgical robots
T2 - 46th IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016
AU - Alemzadeh, Homa
AU - Chen, Daniel
AU - Li, Xiao
AU - Kesavadas, Thenkurussi
AU - Kalbarczyk, Zbigniew T.
AU - Iyer, Ravishankar K.
N1 - Publisher Copyright: © 2016 IEEE.
PY - 2016/9/29
Y1 - 2016/9/29
N2 - This paper demonstrates targeted cyber-physical attacks on teleoperated surgical robots. These attacks exploit vulnerabilities in the robot's control system to infer a critical time during surgery to drive injection of malicious control commands to the robot. We show that these attacks can evade the safety checks of the robot, lead to catastrophic consequences in the physical system (e.g., sudden jumps of robotic arms or system's transition to an unwanted halt state), and cause patient injury, robot damage, or system unavailability in the middle of a surgery. We present a model-based analysis framework that can estimate the consequences of control commands through real-time computation of robot's dynamics. Our experiments on the RAVEN II robot demonstrate that this framework can detect and mitigate the malicious commands before they manifest in the physical system with an average accuracy of 90%.
AB - This paper demonstrates targeted cyber-physical attacks on teleoperated surgical robots. These attacks exploit vulnerabilities in the robot's control system to infer a critical time during surgery to drive injection of malicious control commands to the robot. We show that these attacks can evade the safety checks of the robot, lead to catastrophic consequences in the physical system (e.g., sudden jumps of robotic arms or system's transition to an unwanted halt state), and cause patient injury, robot damage, or system unavailability in the middle of a surgery. We present a model-based analysis framework that can estimate the consequences of control commands through real-time computation of robot's dynamics. Our experiments on the RAVEN II robot demonstrate that this framework can detect and mitigate the malicious commands before they manifest in the physical system with an average accuracy of 90%.
KW - Cyber-physical systems
KW - Malware
KW - RAVEN II robot
KW - Robotic Surgery
KW - Targeted Attacks
KW - Telerobotics
UR - https://www.scopus.com/pages/publications/84994301759
U2 - 10.1109/DSN.2016.43
DO - 10.1109/DSN.2016.43
M3 - Conference contribution
T3 - Proceedings - 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016
SP - 395
EP - 406
BT - Proceedings - 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 28 June 2016 through 1 July 2016
ER -