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

机译:强大的密码系统,可以增强基于语音的人身份验证的安全性

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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 Deoxyri-bonucleic 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.
机译:技术的发展使我们利用言语作为验证人员的生物识别。本文介绍了语音加密和解密算法,用于增强基于语音的人身份验证系统中的安全性。身份验证系统的实现包含用于验证该人的特征提取,建模技术和测试程序。首先,从训练语音话语中提取MEL频率谱系距(MFCC)特征,为每个扬声器开发模型。语音加密系统加密测试语音话语。开发了多种混沌映射技术和脱氧酚醛酚(DNA)添加基于语音密码系统,以确保攻击的测试言论。语音加密系统涉及作为输入的采样测试语音信号,其经受帧内级别和级别的位替换。将这些所得样品被编码为由P(n)表示的DNA序列。 DNA序列P(n)和DNA序列{a(n),b(n),c(n),d(n)}使用基于混沌的不同技术获得,例如帐篷映射,henon映射,正弦映射,使用DNA加法操作和逻辑映射和总结在一起。最后,使用DNA解码获得加密的测试语音。接收侧的扬声器认证系统解密加密信号并从解密的语音中识别扬声器。相关系数测试,信噪比测试,峰值信号到噪声比测试,关键灵敏度测试,NSCR和UACI测试,关键空间分析和直方图分析是用作指标以证明提出的密码系统效率的技术。对于原始测试语音集和解密的测试语音集,文本依赖者身份验证的整体单个精度为97%。对于原始测试语音集和解密的测试语音集,文本独立人员身份验证总体的个人精度为66%。在我们的工作中,语音话语是从AVSPOOF数据库获取的,用于验证44个扬声器。我们的工作突出了加密系统的效率,为测试语音和人员身份验证提供了使用语音作为生物识别的安全性。

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