Turkish Journal of Electrical Engineering and Computer Sciences
DOI
10.3906/elk-1808-161
Abstract
In this paper, we present an efficient retrieval algorithm for encrypted speech based on an inverse fast Fourier transform and measurement matrix. Our approach improves query performance, as well as retrieval efficiency and accuracy, compared to existing content-based encrypted speech retrieval methods. Our proposed algorithm constructs a perceptual hash scheme using perceptual hash sequences from original speech files. By classifying the sequences and applying run-length compression, we decrease the cloud storage required for the hash index. We secure the speech database by encrypting it with Henon chaos scrambling, which offers excellent resistance to attacks. Experimental results show that the robustness, discrimination, and feature extraction efficiency of our proposed method are better than the existing alternatives, with good recall and precision ratios and with high retrieval efficiency and accuracy.
Keywords
Encrypted speech retrieval, perceptual hashing, inverse fast Fourier transform, measurement matrix, Henon chaotic scrambling, speech feature extraction
First Page
1719
Last Page
1736
Recommended Citation
ZHANG, QIUYU; GE, ZIXIAN; ZHOU, LIANG; and ZHANG, YONGBING
(2019)
"An efficient retrieval algorithm of encrypted speech based on inverse fast Fourier transform and measurement matrix,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 27:
No.
3, Article 12.
https://doi.org/10.3906/elk-1808-161
Available at:
https://journals.tubitak.gov.tr/elektrik/vol27/iss3/12
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons
