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 the attackers' main goal is to steer the network's final state to a state of their choice. We show that the detection metric of the straightforward attack scheme proposed by Wu et. at in [1], is vulnerable to a more sophisticated attack. To overcome this attack we propose a novel metric that can be computed locally by each agent to detect the presence of an attacker in the network, as well as a metric that localizes the attackers in the network. We conclude the paper with simulations supporting our findings.
Original language | English |
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Title of host publication | 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538663783 |
DOIs | |
State | Published - 2 Jul 2018 |
Externally published | Yes |
Event | 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 - Eilat, Israel Duration: 12 Dec 2018 → 14 Dec 2018 |
Publication series
Name | 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 |
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Conference
Conference | 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 |
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Country/Territory | Israel |
City | Eilat |
Period | 12/12/18 → 14/12/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- Convex optimization
- Data injection attacks
- Decentralized optimization
- Distributed projected gradient
- Maximum likelihood