TY - GEN
T1 - Multi-agent system for detecting false data injection attacks against the power grid
AU - Amullen, Esther
AU - Lin, Hui
AU - Kalbarczyk, Zbigniew
AU - Keel, Lee
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/12/6
Y1 - 2016/12/6
N2 - A class of cyber-attacks called False Data Injection attacks that target measurement data used for state estimation in the power grid are currently under study by the research community. These attacks modify sensor readings obtained from meters with the aim of misleading the control center into taking ill-advised response action. It has been shown that an attacker with knowledge of the network topology can craft an attack that bypasses existing bad data detection schemes (largely based on residual generation) employed in the power grid. We propose a multi-agent system for detecting false data injection attacks against state estimation. The multi-agent system is composed of software implemented agents created for each substation. The agents facilitate the exchange of information including measurement data and state variables among substations. We demonstrate that the information exchanged among substations, even untrusted, enables agents cooperatively detect disparities between local state variables at the substation and global state variables computed by the state estimator. We show that a false data injection attack that passes bad data detection for the entire system does not pass bad data detection for each agent.
AB - A class of cyber-attacks called False Data Injection attacks that target measurement data used for state estimation in the power grid are currently under study by the research community. These attacks modify sensor readings obtained from meters with the aim of misleading the control center into taking ill-advised response action. It has been shown that an attacker with knowledge of the network topology can craft an attack that bypasses existing bad data detection schemes (largely based on residual generation) employed in the power grid. We propose a multi-agent system for detecting false data injection attacks against state estimation. The multi-agent system is composed of software implemented agents created for each substation. The agents facilitate the exchange of information including measurement data and state variables among substations. We demonstrate that the information exchanged among substations, even untrusted, enables agents cooperatively detect disparities between local state variables at the substation and global state variables computed by the state estimator. We show that a false data injection attack that passes bad data detection for the entire system does not pass bad data detection for each agent.
UR - http://www.scopus.com/inward/record.url?scp=85014848136&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85014848136&partnerID=8YFLogxK
U2 - 10.1145/3018981.3018987
DO - 10.1145/3018981.3018987
M3 - Conference contribution
AN - SCOPUS:85014848136
T3 - ACM International Conference Proceeding Series
SP - 38
EP - 44
BT - Proceedings - 2nd Annual Industrial Control System Security Workshop, ICSS 2016
PB - Association for Computing Machinery
T2 - 2nd Annual Industrial Control System Security Workshop, ICSS 2016
Y2 - 6 December 2016
ER -