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

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.