Perception-Based Audio Authentication Watermarking in the Time-Frequency Domain

Digital audio has been ubiquitous over the past decade. Since it can be easily modified by editing tools, there has been a strong need to protect its content for secure multimedia applications. Existing audio authentication algorithms are mainly focused on either human speech or general audio with music as part of the test data, while special research on music authentication has been somewhat neglected. In this article, we propose a novel algorithm to protect the integrity and authenticity of music signals. Its main contributions include: (1) Music is segmented into beat-based frames, which not only endows the authentication units with more semantic meaning but also perfectly resolves the challenging synchronization problem; (2) Robust hashes are generated from Chroma-based mid-level audio feature which can appropriately characterize the music content, and integrated with an encryption procedure to ensure the security against malicious block-wise vector quantization attack; (3) Fuzzy logic is adopted to make the authentication decision in light of three measures defined on bit errors, coinciding with the inherent blurred nature of authentication. Experiments exhibit good discriminative ability between admissible and malicious operations.

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“…The final decision measure and rules are defined in Eq. (7)(8). If , the dubious music is judged as authentic and otherwise inauthentic.…”

Section: Content Authenticity Verificationmentioning

confidence: 99%

“…To the authors' knowledge, we are not aware of any previous work concentrated on music authentication. Most algorithms are focused on speech authentication [1][2][3][4] or general audio authentication [5][6][7][8][9]. In the latter case some algorithms take music signals as part of the test data.…”

Section: Introductionmentioning

confidence: 99%

On the music content authentication

Zhu

Wang

2012

Proceedings of the 20th ACM International Conference on Multimedia

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“…Alternative reversible hiding methods have been studied [1], [2], [3], [4], [5], [6]. Methods have also been proposed to detect audible modifications or to identify usages [7], [8], [9]. Technologies utilized to verify the integrity of the transmitted speech signal [10], enhance the security of speaker identification system [11], and etc.…”

Section: A Previous Studiesmentioning

confidence: 99%

A New Approach of Reversible Acoustic Steganography for Tampering Detection

Huang

Echizen

Nishimura

2010

2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing

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Progress in signal-processing technology has increased the possibility of malicious attacks and tampering with digital content. We propose a new approach that uses steganography for tampering detection and reversible data hiding. We compute the feature value of the cover data. After applying an Integer Discrete Cosine Transform (intDCT) Type-IV to the cover data, we use amplitude expansion in the high-frequency spectrum to create an embedding space for the feature data and extra payload data in the DCT domain. The extracted feature data are compared with the original hash value to determine if there has been any malicious modification. The adaptive amplitude optimization prevents overflow and underflow of the amplitudes of the stego signal while preserving the reversibility property of the system. Cover data (original audio) are reversible and available if required. This scheme is meant to protect acoustic data of probative importance from illegal usage and to detect any malicious tampering.

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“…In the literature, only few audio authentication algorithms have been published [1][2][3][4][5][6]. One desirable feature of audio authentication is to determine authenticity of a received segment [7].…”

Section: Introductionmentioning

confidence: 99%

Towards content-based audio fragment authentication

Xue

Yin

2011

Proceedings of the 19th ACM International Conference on Multimedia

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Audio authentication is a technique to protect the integrity and originality of audio signals. Due to the long duration, it is often desirable to authenticate only a segment of audio signal. To the authors' knowledge, this important issue has not been seriously researched so far. In this paper, a novel authentication algorithm is proposed for the purpose of audio fragment authentication. SIFT descriptor originated from computer vision field is introduced and calculated on audio spectrogram to accomplish the tasks of fragment alignment, time-domain blocking, cropping and inserting identification etc. Experiments show reliable discrimination between admissible and malicious manipulations, precise tamper localization and classification.

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Perception-Based Audio Authentication Watermarking in the Time-Frequency Domain

Cited by 9 publications

References 13 publications

On the music content authentication

On the music content authentication

A New Approach of Reversible Acoustic Steganography for Tampering Detection

Towards content-based audio fragment authentication

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