Security Versus Privacy
F Farokhi, PM Esfahani
2018 IEEE Conference on Decision and Control (CDC) | IEEE | Published : 2019
© 2018 IEEE. Linear queries can be submitted to a server containing private data. The server provides a response to the queries systematically corrupted using an additive noise to preserve the privacy of those whose data is stored on the server. The measure of privacy is inversely proportional to the trace of the Fisher information matrix. It is assumed that an adversary can inject a false bias to the responses. The measure of the security, capturing the ease of detecting the presence of the false data injection, is the sensitivity of the Kullback-Leiber divergence to the additive bias. An optimization problem for balancing privacy and security is proposed and subsequently solved. It is show..View full abstract
Awarded by Defence Science and Technology Group (DSTG)
Awarded by Swiss National Science Foundation
The work of F. Farokhi was supported by the McKenzie Fellowship from the University of Melbourne, the VESKI Victoria Fellowship from the Victorian State Government, and a grant (MyIP: ID6874) from Defence Science and Technology Group (DSTG). The work of P. Mohajerin Esfahani was supported by the Swiss National Science Foundation under the grant P2EZP2 165264.