TY - GEN
T1 - Cyber and Physical Anomaly Detection in Smart-Grids
AU - Marino, Daniel L.
AU - Wickramasinghe, Chathurika S.
AU - Amarasinghe, Kasun
AU - Challa, Hari
AU - Richardson, Philip
AU - Jillepalli, Ananth A.
AU - Johnson, Brian K.
AU - Rieger, Craig
AU - Manic, Milos
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - The inclusion of Information and Communication Technologies (ICTs) in industrial control systems (ICSs) has opened ICSs to several attack vectors, which are increasingly targeting critical infrastructure. Accurate detection and distinction between benign physical disturbances, malicious cyber-attacks, and malicious physical-attacks are necessary to protect critical infrastructure. While cyber sensors provide a useful tool to identify and mitigate cyber attacks, they often ignore the physical behavior of the system at hand. In this paper, we present a cyber-physical sensor called IREST (ICS Resilient Security Technology). The sensor takes a holistic approach in detecting anomalies by considering both cyber and physical disturbances in a complex system. The sensor was tested under different cyber-physical scenarios using the Idaho CPS SCADA Cybersecurity (ISAAC) testbed. The test scenarios capture different operational states of the CPS testbed, including various cyber and physical anomalies. The experiments show that the IREST sensor is able to detect both cyber and physical anomalies. The sensor has the benefit that training requires only normal data and is able to detect disturbances that have not been seen before. The presented approach provides a scalable framework for cyber-physical security research that can be expanded in the future.
AB - The inclusion of Information and Communication Technologies (ICTs) in industrial control systems (ICSs) has opened ICSs to several attack vectors, which are increasingly targeting critical infrastructure. Accurate detection and distinction between benign physical disturbances, malicious cyber-attacks, and malicious physical-attacks are necessary to protect critical infrastructure. While cyber sensors provide a useful tool to identify and mitigate cyber attacks, they often ignore the physical behavior of the system at hand. In this paper, we present a cyber-physical sensor called IREST (ICS Resilient Security Technology). The sensor takes a holistic approach in detecting anomalies by considering both cyber and physical disturbances in a complex system. The sensor was tested under different cyber-physical scenarios using the Idaho CPS SCADA Cybersecurity (ISAAC) testbed. The test scenarios capture different operational states of the CPS testbed, including various cyber and physical anomalies. The experiments show that the IREST sensor is able to detect both cyber and physical anomalies. The sensor has the benefit that training requires only normal data and is able to detect disturbances that have not been seen before. The presented approach provides a scalable framework for cyber-physical security research that can be expanded in the future.
KW - Anomaly Detection
KW - Cyber-physical systems
KW - Machine Learning
KW - SCADA
UR - https://www.scopus.com/pages/publications/85079327163
U2 - 10.1109/RWS47064.2019.8972003
DO - 10.1109/RWS47064.2019.8972003
M3 - Conference contribution
AN - SCOPUS:85079327163
T3 - Proceedings - 2019 Resilience Week, RWS 2019
SP - 187
EP - 193
BT - Proceedings - 2019 Resilience Week, RWS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Resilience Week, RWS 2019
Y2 - 4 November 2019 through 7 November 2019
ER -