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On Confidentiality Preserving Monitoring of Linear Dynamic Networks Against Inference Attacks

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date3/07/2015
Host publicationAmerican Control Conference
PublisherIEEE
Pages359-364
Number of pages5
ISBN (electronic)9781479986842
<mark>Original language</mark>English
Event2015 American Control Conference (ACC) - Hilton Palmer House, Chicago, United States
Duration: 1/07/20153/07/2015
https://ieeexplore.ieee.org/xpl/conhome/7160954/proceeding

Conference

Conference2015 American Control Conference (ACC)
Country/TerritoryUnited States
CityChicago
Period1/07/153/07/15
Internet address

Conference

Conference2015 American Control Conference (ACC)
Country/TerritoryUnited States
CityChicago
Period1/07/153/07/15
Internet address

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.