Information-Theoretic Analysis of Privacy Protection for Noisy Identification Based on Soft Fingerprinting

TL;DRAbstract

Identification of contents or objects based on some data that are stored/distributed in public domain is required in various applications. At the same time, these data should not reveal any information about original content or object that may be missused in terms of privacy leakage. We consider a privacy protection strategy based on reliable components of data and investigate the performance of this scheme with respect to achievable identification rate and privacy leak. The data stored/distributed in the public domain are binary, while the encoder and the decoder operate with real data. The advocated strategy is referred to as soft fingerprinting.

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