Maintained by
Qi Li, Hui Zhu, Xiaopeng Yang, Rongxing Lu, Ziling Zhang, and Hui Li
Xidian University
266 Xinglong Section of Xifeng Road, Xi’an, Shaanxi 710126, China


With the booming of Internet of Things (IoT) and intelligent terminals, the applications of speaker recognition have been seen increasingly rapid advances in the past two decades. However, the flourish of speaker recognition technology still faces many challenges in IoT scenarios, especially in preventing the disclosure of voiceprint. In this paper, aiming at addressing the challenges, an efficient and privacy-preserving speaker recognition scheme, named AGREE, is proposed for IoT. With AGREE, the speaker identity can be recognized at multiple security levels while without leaking the voiceprint data. To be specific, based on the random matrix theory, a voiceprint encryption algorithm and the corresponding ciphertext-based similarity computation algorithm are proposed. Resting upon these algorithms, our efficient and accurate speaker recognition AGREE scheme can be achieved. Detailed analysis shows that AGREE can resist various known security threats. In addition, AGREE has also been implemented with a real speaker voiceprint dataset, and extensive simulation results demonstrate that AGREE is highly accurate and efficient, and can be flexibly deployed in real environment.

  System Model

  Overview of AGREE


(a) The accuracy of no protection scheme, PPiSV, HESR and AGREE.

(b) The accuracy of AGREE with σ=0,10,15.

  Computational Complexity

Recognition computation time in no protection scheme, AGREE, PPiSV and HESR.

Computation overhead of AGREE.

  Demo Download

Demo Download:  
Demo File SHA256: 0A0B41D0455B0CC9DE846C217067027C940B562CDC43CECD094057832D5DEB6E
For Source Code:    zhuhui@xidian.edu.cn