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Stream/Area:
-
Subject:
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Paper ID:
10.55041/IJSREM.NCFT043
Volume:
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Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
To enhance the privacy and security of audio signals stored in third-party storage centers, a robust digital audio encryption and forensics watermarking scheme is proposed. The scheme incorporates the AES-GCM (Advanced Encryption Standard in Galois/Counter Mode) algorithm for authenticated encryption, ensuring both confidentiality and integrity of the audio data. In addition, we utilize Fernet symmetric encryption and PBKDF2HMAC (Password-Based Key Derivation Function 2 with HMAC) for key generation, supported by generative hash passwords to further strengthen security. The signal energy ratio feature of audio signals is defined and used in the watermark embedding method through feature quantification, improving the resilience of the watermarking system. First, the original audio is encrypted using scrambling, multiplication, and AES-GCM to generate the encrypted data. The encrypted data is then divided into frames, each compressed through sampling. The compressed data, along with frame numbers, is embedded into the encrypted audio, forming the watermarked signal which is uploaded to third-party storage. Authorized users retrieve the encrypted data and verify its authenticity. If intact,the data is decrypted directly using Fernet to recover the original audio. In the case of an attack,the compromised frames are identified, and the embedded compressed data is used to reconstruct the audio approximately. The reconstructed signal is subsequently decrypted to retain the expression meaning of the original audio. Experimental results demonstrate the effectiveness of the proposed scheme in providing quantum-safe encryption, secure watermarking, and forensics capabilities.
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Publication Date
6/17/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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