A retrieval algorithm for encrypted speech based on perceptual hashing

Abstract

In order to further improve the robustness and discrimination of perceptual hashing and retrieval speed in large-scale data, a novel retrieval algorithm over encrypted speech is proposed. Before encrypted speech is uploaded, perceptual hashing sequences must be embedded as a digital watermark. In the process of generating perceptual hashing, multifractal characteristic of speech that has good distinctiveness and robustness is introduced, and the technology of piecewise aggregate approximation is used for compressing data size. The retrieval process does not need decryption but requires the generation of perceptual hashing sequence of query speech segment. Each perceptual hashing set in system hash table should then be matched successively. Experimental results indicate that the perceptual hashing generated from multifractal characteristics shows better distinctiveness and robustness than those derived from time and frequency domain features in existing methods. Furthermore, because of employing the technology of piecewise aggregate approximation, the generated perceptual hashing has small amounts of data, which leads to the greatly improvement of retrieval speed. And finally, the proposed retrieval algorithm achieves high recall and precision ratios in terms of the variety of content holding operation.