Efficient audio integrity verification algorithm using discrete cosine transform |
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Authors: | 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 |
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Affiliation: | 1.Nuclear Research Center,Atomic Energy Authority of Egypt,Cairo,Egypt;2.Faculty of Electronic Engineering, Department of Computer Science and Engineering,Menoufia University,Menouf,Egypt;3.Faculty of Engineering, Department of Electrical Engineering,Menoufia University,Shebin El-kom,Egypt;4.Department of Communication Technology, Faculty of Industrial Education,Helwan University,Cairo,Egypt;5.Faculty of Electronic Engineering, Department of Electronics and Electrical Communications,Menoufia University,Menouf,Egypt;6.Department of Information Technology, College of Computers and Information Technology,Taif University,Al-Hawiya,Kingdom of Saudi Arabia |
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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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