On Confidentiality Preserving Monitoring of Linear Dynamic Networks Against Inference Attacks

Lu, Yang (2015) On Confidentiality Preserving Monitoring of Linear Dynamic Networks Against Inference Attacks. In: American Control Conference. IEEE, USA, pp. 359-364. ISBN 9781479986842

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Abstract

Distributed information sharing in dynamic networks is ubiquitous. It raises the concern that confidential information of dynamic networks could be leaked to malicious entities and further exploited in direct attacks. In this paper, we formulate the problem of competitive confidentiality preserving monitoring of linear dynamic networks against inference attacks. We show that the unstructured ℓ 0 minimization is NP-hard. We then provide a SDP equivalence for the structured ℓ 2 minimization.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
172578
Deposited By:
Deposited On:
15 Jul 2022 15:30
Refereed?:
Yes
Published?:
Published
Last Modified:
13 Sep 2022 01:36