Record Details
Field | Value |
---|---|
Title | Subspace Methods for Data Attack on State Estimation: A Data Driven Approach |
Names |
Kim, Jinsub
(creator) Tong, Lang (creator) Thomas, Robert J. (creator) |
Date Issued | 2015-03-01 (iso8601) |
Note | This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE-Institute of Electrical and Electronics Engineers and can be found at: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=78 |
Abstract | Data attacks on state estimation modify part of system measurements such that the tempered measurements cause incorrect system state estimates. Attack techniques proposed in the literature often require detailed knowledge of system parameters. Such information is difficult to acquire in practice. The subspace methods presented in this paper, on the other hand, learn the system operating subspace from measurements and launch attacks accordingly. Conditions for the existence of an unobservable subspace attack are obtained under the full and partial measurement models. Using the estimated system subspace, two attack strategies are presented. The first strategy aims to affect the system state directly by hiding the attack vector in the system subspace. The second strategy misleads the bad data detection mechanism so that data not under attack are removed. Performance of these attacks are evaluated using the IEEE 14- bus network and the IEEE 118-bus network. |
Genre | Article |
Topic | state estimation |
Identifier | Kim, J., Tong, L., & Thomas, R. J. (2015). Subspace Methods for Data Attack on State Estimation: A Data Driven Approach. IEEE Transactions on Signal Processing, 63(5), 1102-1114. doi:10.1109/TSP.2014.2385670 |