Faragallah, Osama SAbd El-Samie, Fathi EEl-Bendary, Mohsen A. MEl-sayed, Hala SKelash, Hamdy MAyad, Nabil MNassar, Sabry S2019-12-142019-12-142016-03DISCRETE COSINE TRANSFORM By: AHMED, N; NATARAJAN, T; RAO, KR IEEE TRANSACTIONS ON COMPUTERS Volume: C 23 Issue: 1 Pages: 90-93 Published: 1974 Times Cited: 1,796 2. Title: [not available] By: ALHAJ A P 1 INT C NETW DIG T Pages: 398 Published: 2009 Times Cited: 1 3. Robust audio watermarking in the time domain By: Bassia, P; Pitas, I; Nikolaidis, N IEEE TRANSACTIONS ON MULTIMEDIA Volume: 3 Issue: 2 Pages: 232-241 Published: JUN 2001 Times Cited: 260 4. A novel spread spectrum digital audio watermarking technique By: Can, Y.S.; Alagoz, F.; Burus, M.E. Journal of Advances in Computer Networks Volume: 2 Issue: 1 Pages: 6-9 Published: March 2014 Times Cited: 4 5. Semi-fragile watermarking for image authentication, localization, and recovery using Tchebi-chef moments By: Chang, W. H.; Chang, L. W. 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Speech content integrity verification integrated with ITU G.723.1 speech coding By: Wu, CP; Kuo, CCJ INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY: CODING AND COMPUTING, PROCEEDINGS Pages: 680-684 Published: 2001 Times Cited: 13 24. Title: [not available] By: YANG WH ACOUST SPEECH SIG PR Pages: 541 Published: 1998 Times Cited: 16 25. Robust and transparent audio watermarking based on improved spread spectrum and psychoacoustic masking By: Zhang, P.; Xu, S.; Yang, H. P IEEE INT C INF SCI Pages: 640-643 Published: 20121381-2416https://doi.org/10.1007/s10772-015-9312-6https://dl.acm.org/citation.cfm?id=2890455Accession Number: WOS:000377290700001Audio 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.en-USUniversity for QUALITYWATERMARKINGDCTDigital WatermarkingIntegrityArticlehttps://doi.org/10.1007/s10772-015-9312-6