@inproceedings{ab9c00e470e842398588e055e0c945b4,
title = "Localization of Data Injection Attacks on Distributed M-Estimation",
abstract = "This paper describes a distributed statistical estimation problem, corresponding to a network of agents. The network may be vulnerable to data injection attacks, in which attackers control legitimate nodes in the network and use them to inject false data. We have previously shown [1] that the detection metric by Wu et. al in [2], is vulnerable to sophisticated attacks where the attacker mixes normal behaviour and false data injection. In this paper we propose a novel metric that can be computed locally by each agent to detect and localize the novel attack in the network in a single instance.",
keywords = "Convex optimization, Data injection attacks, Decentralized optimization, Distributed projected gradient, M-Estimators",
author = "Or Shalom and Amir Leshem and Anna Scaglione",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Data Science Workshop, DSW 2019 ; Conference date: 02-06-2019 Through 05-06-2019",
year = "2019",
month = jun,
doi = "10.1109/DSW.2019.8755572",
language = "الإنجليزيّة",
series = "2019 IEEE Data Science Workshop, DSW 2019 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "22--26",
booktitle = "2019 IEEE Data Science Workshop, DSW 2019 - Proceedings",
address = "الولايات المتّحدة",
}