@inproceedings{ad6c5d2884724baf9d3f6d2d81c15880,
title = "Cyber attack localization in smart grids by graph modulation",
abstract = "In this brief announcement we present our ongoing work to localize “false data injection” (FDI) attacks on the system state of modern power systems, better known as smart grids. Because of their exceptional importance for our society and together with the increasing presence of information and telecommunication (ICT) components, these power systems are a vulnerable target for cyber attacks. In our method, we represent the power system as a graph and use a generalized modulation operator that is applied on the states of the system. Our preliminary results indicate that attacked grid states exhibit specific modulation patterns that facilitate the localization of the attacks on the particular buses of the grid. This approach is demonstrated by several case study simulations.",
keywords = "Anomaly detection, False data injection (FDI) attacks, Graph signal processing, Laplacian matrix, Smart grid",
author = "Elisabeth Drayer and Tirza Routtenberg",
note = "Funding Information: Supported by the Kreitman School of Advanced Graduate Studies and the BGU Cyber Security Research Center. Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 3rd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2019 ; Conference date: 27-06-2019 Through 28-06-2019",
year = "2019",
month = may,
day = "19",
doi = "10.1007/978-3-030-20951-3_8",
language = "English",
isbn = "9783030209506",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "97--100",
editor = "Shlomi Dolev and Danny Hendler and Sachin Lodha and Moti Yung",
booktitle = "Cyber Security Cryptography and Machine Learning - 3rd International Symposium, CSCML 2019, Proceedings",
address = "Germany",
}