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Erschienen in: International Journal of Speech Technology 1/2016

12.11.2015

Efficient audio integrity verification algorithm using discrete cosine transform

verfasst von: Sabry S. Nassar, Nabil M. Ayad, Hamdy M. Kelash, Hala S. El-sayed, Mohsen A. M. El-Bendary, Fathi E. Abd El-Samie, Osama S. Faragallah

Erschienen in: International Journal of Speech Technology | Ausgabe 1/2016

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Abstract

Audio recordings have been used as evidence for long times. Multimedia processing advancement makes it difficult to be completely sure about what is heard is the truth. This paper presents a promising approach for integrity verification of recorded audio signals using discrete cosine transform. This approach is based on self embedding concept which embeds block-based marks extracted from the same audio signal after being transformed into 2-D format into other blocks according to a specific algorithm. After the self-embedding process, the data is converted back into 1-D style which represents a marked audio signal. The 1-D audio signal is converted into a 2-D format and then converted back into a 1-D format using the popular lexicographic ordering scheme utilized in image processing. Reverse processes are executed to extract the verification marks from the audio signal throughout the integrity verification process. Based on the extracted audio signal properties, the integrity of the marked audio signal is evaluated. Different audio processing tasks and attacks are implemented to examine the suitability of the proposed algorithm for verifying the integrity of high-confidentiality recorded audio data. The results show that the efficient ability of the proposed approach to verify integrity and detect attacks.

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Metadaten
Titel
Efficient audio integrity verification algorithm using discrete cosine transform
verfasst von
Sabry S. Nassar
Nabil M. Ayad
Hamdy M. Kelash
Hala S. El-sayed
Mohsen A. M. El-Bendary
Fathi E. Abd El-Samie
Osama S. Faragallah
Publikationsdatum
12.11.2015
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 1/2016
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-015-9312-6

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