Localization of sparse image tampering via random projections

Hashes can be used to provide authentication of multimedia con-tents. In the case of images, a hash can be used to detect whether the data has been modified in an illegitimate way. When the authentica-tion check fails, it might be useful to localize the tampering in the spatial domain. This paper proposes an algorithm based on compres-sive sensing principles, which solves both the authentication and the localization problems. The encoder produces a hash using a small bit budget by quantizing a limited number of random projections of the authentic image. The decoder uses the hash to estimate the distortion between the original and the received image. In addition, if the at-tack is sparse, it can be also localized. In order to keep the size of the hash small, encoding/decoding takes advantage of distributed source codes. This paper also investigates experimentally the tradeoff be-tween the rate allocated to the hash and the performance achieved in terms of tampering localization. Index Terms — Image tampering, compressive sensing, dis-tributed source codin