Unified Expression of Utility-Privacy Trade-off in Privacy-Constrained Source Coding
Naruki Shinohara, Hideki Yagi

TL;DR
This paper develops a unified theoretical framework using rate-distortion theory to characterize the utility-privacy trade-off in privacy-constrained source coding, encompassing previous special cases and highlighting the importance of encoding choices.
Contribution
It introduces a comprehensive rate-distortion-based expression for the utility-privacy trade-off in the general case where encoded messages include both public and private information.
Findings
The unified expression includes previous special cases as subsets.
Numerical results show optimal encoding strategies vary with the scenario.
Neither of the previous specific cases always yields the best trade-off.
Abstract
Privacy-constrained source coding problems have become increasingly important recently, and the utility-privacy trade-off has been investigated for various systems. As pioneering work, Yamamoto (1983) found theoretical limits of the coding rate, privacy and utility in two cases; (i) both public and private information is encoded and (ii) only public information is encoded. However, the theoretical limit has not been characterized in a more general case; (iii) encoded messages consist of public information and a part of private information. Then in this paper, we characterize the trade-off relation in case (iii) using rate-distortion theory. The obtained expression of the achievable region is a "unified expression" because it includes the ones in cases (i) and (ii) as special cases. The numerical results also demonstrate that neither case (i) nor (ii) are the best cases, and it is…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsWireless Communication Security Techniques · DNA and Biological Computing · Energy Harvesting in Wireless Networks
