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1

Detection of Montage in Lossy Compressed Digital Audio Recordings

Korycki R.

Archives of Acoustics

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2014

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Vol. 39, No. 1

65--72

EN

This paper addresses the problem of tampering detection and discusses methods used for authenticity analysis of digital audio recordings. Presented approach is based on frame offset measurement in audio files compressed and decoded by using perceptual audio coding algorithms which employ modified discrete cosine transform. The minimum values of total number of active MDCT coefficients occur for frame shifts equal to multiplications of applied window length. Any modification of audio file, including cutting off or pasting a part of audio recording causes a disturbance within this regularity. In this study the algorithm based on checking frame offset previously described in the literature is expanded by using each of four types of analysis windows commonly applied in the majority of MDCT based encoders. To enhance the robustness of the method additional histogram analysis is performed by detecting the presence of small value spectral components. Moreover, computation of maximum values of nonzero spectral coefficients is employed, which creates a gating function for the results obtained based on previous algorithm. This solution radically minimizes a number of false detections of forgeries. The influence of compression algorithms’ parameters on detection of forgeries is presented by applying AAC and Ogg Vorbis encoders as examples. The effectiveness of tampering detection algorithms proposed in this paper is tested on a predefined music database and compared graphically using ROC-like curves.

2

Structural Feature-Based Image Hashing and Similarity Metric for Tampering Detection

Tang Z., Wang S., Zhang X., Wei W.

Fundamenta Informaticae

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2011

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Vol. 106, nr 1

75-91

EN

Structural image features are exploited to construct perceptual image hashes in this work. The image is first preprocessed and divided into overlapped blocks. Correlation between each image block and a reference pattern is calculated. The intermediate hash is obtained from the correlation coefficients. These coefficients are finally mapped to the interval [0, 100], and scrambled to generate the hash sequence. A key component of the hashingmethod is a specially defined similarity metric to measure the "distance" between hashes. This similarity metric is sensitive to visually unacceptable alterations in small regions of the image, enabling the detection of small area tampering in the image. The hash is robust against content-preserving processing such as JPEG compression, moderate noise contamination, watermark embedding, re-scaling, brightness and contrast adjustment, and low-pass filtering. It has very low collision probability. Experiments are conducted to show performance of the proposed method.

3

Methods of Time-Frequency Analysis in Authentication of Digital Audio Recordings

Korycki R.

International Journal of Electronics and Telecommunications

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2010

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Vol. 56, No. 3

257-262

EN

This paper describes the problem of tampering detection and discusses the main methods used for authenticity analysis of digital audio recordings. For the first topic, two frequency measurement algorithms based on electric network frequency criterion are applied. Time-frequency analysis is used and improved with reassignment method for purpose of visual inspection of modified recordings. The algorithms are shortly described and exemplary plots are presented with interpretation. The last described method, recently proposed, is based on checking frame offsets in compressed audio files.