TY - GEN
T1 - A Multi-Means Speech Encryption Algorithm Based on Improved Zigzag Transformation
AU - Wang, Xi
AU - Zhou, Yan
AU - Wang, Jifei
AU - Wang, Qingjuan
AU - Huang, Shan
AU - Xu, Zichao
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The application of deep neural networks has led to a significant increase in the accuracy of automatic speech recognition. When unencrypted speech is transmitted over the Internet, malicious attackers are able to use automatic speech recognition technology to obtain private information from speech, which brings security risks such as personal information leakage and property loss. In this paper, a reversible speech encryption and decryption algorithm is proposed, to realize the encryption and decryption of speech sequences by improving the ZigZag transformation and integrating the Lorenz chaotic map, DNA coding and Arnold map. For encryption, the key of each algorithm is first calculated using the Hash value and external keys. And then, the speech is divided into two parts, they are executed XOR operation separately with the x and y chaotic sequences generated by the Lorenz map. Next, the two parts of the speech are encrypted with DNA coding and Arnold mapping, and a Zigzag rotation is performed respectively before and after splicing the two parts of the speech sequence. Finally, the speech sequence is XOR with the z0 chaotic sequence generated by the Lorenz map, and the final encrypted sequence is obtained. The experiments show that the algorithm proposed in this paper has a large key space, high key sensitivity, and has better performance than the existing algorithms.
AB - The application of deep neural networks has led to a significant increase in the accuracy of automatic speech recognition. When unencrypted speech is transmitted over the Internet, malicious attackers are able to use automatic speech recognition technology to obtain private information from speech, which brings security risks such as personal information leakage and property loss. In this paper, a reversible speech encryption and decryption algorithm is proposed, to realize the encryption and decryption of speech sequences by improving the ZigZag transformation and integrating the Lorenz chaotic map, DNA coding and Arnold map. For encryption, the key of each algorithm is first calculated using the Hash value and external keys. And then, the speech is divided into two parts, they are executed XOR operation separately with the x and y chaotic sequences generated by the Lorenz map. Next, the two parts of the speech are encrypted with DNA coding and Arnold mapping, and a Zigzag rotation is performed respectively before and after splicing the two parts of the speech sequence. Finally, the speech sequence is XOR with the z0 chaotic sequence generated by the Lorenz map, and the final encrypted sequence is obtained. The experiments show that the algorithm proposed in this paper has a large key space, high key sensitivity, and has better performance than the existing algorithms.
KW - Arnold map
KW - DNA coding
KW - Lorenz chaotic map
KW - Speech encryption
KW - Zigzag Transformation
UR - http://www.scopus.com/inward/record.url?scp=85198639752&partnerID=8YFLogxK
U2 - 10.1109/IMCEC59810.2024.10574977
DO - 10.1109/IMCEC59810.2024.10574977
M3 - Conference contribution
AN - SCOPUS:85198639752
T3 - IMCEC 2024 - IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference
SP - 1371
EP - 1377
BT - IMCEC 2024 - IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2024
Y2 - 24 May 2024 through 26 May 2024
ER -