A robust cryptosystem to enhance the security in speech based person authentication

• Published in: Multimedia tools and applications 2020-08, Vol.79 (29-30), p.20795-20819
• Main Authors: Nagakrishnan, R., Revathi, A.
• Format: Article
• Language: English
• Subjects: Algorithms; Biometrics; Computer Communication Networks; Computer Science; Correlation coefficients; Data Structures and Information Theory; Deoxyribonucleic acid; DNA; Encryption; Feature extraction; Gene sequencing; Histograms; Mapping; Multimedia Information Systems; Noise sensitivity; Security; Signal to noise ratio; Special Purpose and Application-Based Systems; Speech; Test procedures
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-020-08846-1

The developments in technology have made us utilizing speech as a biometric to authenticate persons. In this paper, speech encryption and decryption algorithm are presented for enhancing the security in speech-based person authentication systems. The implementation of the authentication system contains the feature extraction, modeling techniques and testing procedures for authenticating the person. Firstly, the Mel frequency cepstral coefficient (MFCC) features are extracted from the training speech utterances and models are developed for each speaker. The speech encryption system encrypts the test speech utterances. Multiple chaotic mapping techniques and Deoxyribonucleic acid (DNA) addition based speech cryptosystem is developed to secure test speech against attacks. The speech encryption system deals with sampled test speech signal given as input, which is subjected to intra level and inter level bit substitution. These resultant samples are encoded into the DNA sequence denoted by P(n). The DNA sequence P(n) and DNA sequences {A(n), B(n), C(n), D(n)} obtained using different techniques based on chaos, such as tent mapping, henon mapping, sine mapping, and logistic mapping and summed up together using DNA addition operation. Finally, the encrypted test speech is obtained using DNA decoding. The speaker authentication system in the receiving side decrypts the encrypted signal and identifies the speakers from the decrypted speech. The correlation coefficient test, Signal to noise ratio test, Peak Signal to Noise Ratio test, key sensitivity test, NSCR and UACI test, key space analysis, and histogram analysis are the techniques used as metrics to prove the efficiency of the proposed cryptosystem. Overall individual accuracy is 97% for the text dependent person authentication with the original test speech set and decrypted test speech set. Overall individual accuracy is 66% for the text independent person authentication with the original test speech set and decrypted test speech set. In our work, the speech utterances are taken from AVSpoof database for authenticating 44 speakers. Our work highlights the efficiency of the encryption system, to provide security for test speech and person authentication using speech as a biometric.