Abstract
Perceptual hash functions provide a tool for fast and reliable identification of content. We present new audio hash functions based on summarization of the time-frequency spectral characteristics of an audio document. The proposed hash functions are based on the periodicity series of the fundamental frequency and on singular-value description of the cepstral frequencies. They are found, on one hand, to perform very satisfactorily in identification and verification tests, and on the other hand, to be very resilient to a large variety of attacks. Moreover, we address the issue of security of hashes and propose a keying technique, and thereby a key-dependent hash function.
Highlights
In this study, we develop algorithms for summarizing a long audio signal into a concise signature sequence, which can be used to identify the original record
We have performed simulation experiments in order to test (i) the robustness of the perceptual hash for identification, where the critical behavior is the statistical spread of the hash function when an audio document is subjected to various signal processing attacks; (ii) the uniqueness of the perceptual hash, where the important behavior is the fact that the hashes differ significantly between two different contents
We want to classify documents with different contents, so that if we want to verify a document, the others in the database appear as “impostors.” In a decision-theoretic sense, the uniqueness property is related to the probability of false alarm or false alarm rate (FAR), while the robustness property is linked to the probability of misses or false rejection rate (FRR)
Summary
We develop algorithms for summarizing a long audio signal into a concise signature sequence, which can be used to identify the original record. We aim to obtain audio hash functions that are insensitive to “reasonable” signal processing and editing operations, such as filtering, compression, sampling rate conversion and so forth, but that are otherwise sensitive to the change in content. Such perceptual hash functions can be used as a tool to search for a specific record in a database, to verify the content authenticity of the record, to monitor broadcasts, to automatically index multimedia libraries, to. In tamper proofing and data content authentication applications, the hash values of the applicant object are compared with hash values of the stored ones
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