Extended Functional Representation Lemma: A Tool For Privacy, Semantic Representation, Caching, and Compression Design
Amirreza Zamani, Mikael Skoglund

TL;DR
This paper extends the Functional Representation Lemma to aid in designing privacy mechanisms that optimize privacy-utility trade-offs across various scenarios, with applications in semantic communication, caching, and compression.
Contribution
It introduces extended versions of the Functional Representation Lemma to develop low-complexity privacy mechanisms for different privacy constraints and scenarios.
Findings
Extended lemmas facilitate privacy mechanism design.
Achieves optimal privacy-utility trade-offs.
Applicable to semantic communications, caching, and compression.
Abstract
This paper provides an overview of a problem in information-theoretic privacy mechanism design, addressing two scenarios in which private data is either observable or hidden. In each scenario, different privacy measures are used, including bounded mutual information and two types of per-letter privacy constraints. Considering the first scenario, an agent observes useful data that is correlated with private data, and wants to disclose the useful information to a user. Due to the privacy concerns, direct disclosure is prohibited. Hence, a privacy mechanism is designed to generate disclosed data which maximizes the revealed information about the useful data while satisfying a privacy constraint. In the second scenario, the agent has additionally access to the private data. We discuss how the Functional Representation Lemma, the Strong Functional Representation Lemma, and their extended…
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Taxonomy
TopicsPrivacy-Preserving Technologies in Data
