Biohashing encrypted speech retrieval based on chaotic measurement matrix

被引：0
|
作者：
Huang Y. [1 ]
Wang Y. [1 ]
Zhang Q. [2 ]
Chen T. [1 ]
机构：
[1] College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou
[2] School of Computer and Communication, Lanzhou University of Technology, Lanzhou
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2020年 / 48卷 / 12期
关键词：
Biohashing; Biometric template; Encrypted speech retrieval; Improved sha256 algorithm; Rossler chaotic measurement matrix;
D O I：
10.13245/j.hust.201206
中图分类号：
学科分类号：
摘要：
In order to solve the problem of plaintext data leakage in the existing speech retrieval system, and improve the performance of speech retrieval, the security and privacy of biometric template, a biohashing encrypted speech retrieval algorithm was proposed based on Rossler chaotic measurement matrix.First, the speech was classified by the client, and redistribute key with class as single mapping.A 358 bit Rossler chaotic measurement matrix was generated by the key, the matrix was used to transform the speech features, and the hash index of speech was generated by binarization.Then the speech file was encrypted using the improved sha256 algorithm.Finally, hash index and encrypted speech were sent to the cloud.The experimental results show that this algorithm not only can effectively prevent plaintext leakage, but also has good robustness, discrimination and retrieval performance.At the same time, biometric template has good diversity, revocability, security and privacy. © 2020, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
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页码：32 / 37
页数：5
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