On confidentiality preserving monitoring of linear dynamic networks against inference attacks

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 ℓ₀ minimization is NP-hard. We then provide a SDP equivalence for the structured ℓ₂ minimization.