A secure marine mammal audio retrieval algorithm based on deep biohashing
Year: 2025
Type: article
Abstract: Marine mammals are crucial subjects for marine audio studies, particularly in the development of retrieval algorithms for encrypted marine mammal audio. To address the issues of low retrieval performance and insufficient expression of audio features, and to ensure the security of existing audio retrieval algorithms, this paper proposes a secure marine mammal audio retrieval algorithm based on deep biohashing. The server terminal utilizes the BiGRU-Residual-Multi-Head-Self-Attention (BiGRU-RMHSA) autoencoder model to extract the deep features of dynamic Gammatone Cepstral Coefficients (GTCC), which improves robustness and discrimination of retrieval algorithm. Then, the classified deep features and the corresponding orthogonal matrix construct the key-controlled biosafety template to reduce the leakage of deep features. Finally, the template is quantified to obtain the biohashing. Meanwhile, the chaotic DNA encryption scheme encrypts audio to ensure audio security. The experiments show that the retrieval scheme has higher precision and recall for different content preserving operations. And the proposed encryption scheme reduces the audio correlation and its key space is 10 80 , ensuring the resistance of encrypted audio to statistical attacks. Furthermore, the biosafety template has better revocability, security and diversity.
Source: Applied Acoustics
Institution: Hainan University
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,820
OpenAlex ID: W7093316016