TY - GEN
T1 - Diagnosis of Safety Incidents for Cyber-Physical Systems
T2 - 3rd International Conference on System Reliability and Safety, ICSRS 2018
AU - Zibaei, Ehsan
AU - Banescu, Sebastian
AU - Pretschner, Alexander
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/4/11
Y1 - 2019/4/11
N2 - As capabilities of cyber-physical systems (CPS) increase, the interaction of software and physical components becomes more complicated. When a CPS encounters an incident, the increased complexity makes diagnosis a challenging task for traditional diagnostic approaches. To overcome this problem, we split the diagnostic procedure into three steps, namely: (1) type causality, (2) detection and (3) actual causality analyses. We then utilize various technologies to automate each step. Fault trees are extracted from the four variable model of a CPS. This results in modular and human-readable fault trees. Moreover, CPS logs are mapped to the instances of the fault tree nodes using time series analysis techniques. Through examples of unmanned aerial vehicles (UAV), we demonstrate that our framework can diagnose a wide range of scenarios including software, sensor, and actuator failures.
AB - As capabilities of cyber-physical systems (CPS) increase, the interaction of software and physical components becomes more complicated. When a CPS encounters an incident, the increased complexity makes diagnosis a challenging task for traditional diagnostic approaches. To overcome this problem, we split the diagnostic procedure into three steps, namely: (1) type causality, (2) detection and (3) actual causality analyses. We then utilize various technologies to automate each step. Fault trees are extracted from the four variable model of a CPS. This results in modular and human-readable fault trees. Moreover, CPS logs are mapped to the instances of the fault tree nodes using time series analysis techniques. Through examples of unmanned aerial vehicles (UAV), we demonstrate that our framework can diagnose a wide range of scenarios including software, sensor, and actuator failures.
KW - automated diagnosis
KW - causality
KW - cyber-physical systems
KW - fault tree analysis
KW - safety
UR - http://www.scopus.com/inward/record.url?scp=85065016396&partnerID=8YFLogxK
U2 - 10.1109/ICSRS.2018.8688886
DO - 10.1109/ICSRS.2018.8688886
M3 - Conference contribution
AN - SCOPUS:85065016396
T3 - Proceedings - 2018 3rd International Conference on System Reliability and Safety, ICSRS 2018
SP - 120
EP - 129
BT - Proceedings - 2018 3rd International Conference on System Reliability and Safety, ICSRS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 November 2018 through 26 November 2018
ER -