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Novel secured speech communication for person authentication

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Abstract

Biometrics is the common method of securely and efficiently identifying and authenticating individuals by using unique biological features. Some common biometrics is fingerprint, speech, iris and signature. In this paper, the cryptosystem is proposed to enhance security and conserve the transmission bandwidth in implementing an authentication system The design of speech based secured authentication systems include the extraction of features from speech, creation of templates and testing procedures to authenticate the persons. The speaker recognition system is formed using Mel Frequency Cepstral coefficients (MFCC) and Recurrent Neural network (RNN) based machine learning technique. For developing a training system, MFCC features are extracted from the training data set. The RNN network is trained with features and a speakers’ template is created for each speaker. In testing phase to ensure security in speech based authentication, MFCC features are extracted from the test speech set and these features are encrypted before it gets transmitted through the unsecured channel. The proposed crypto system is developed based on 3D logistic chaotic map and DNA operation. Firstly, MFCC features derived from the test speech set are concatenated and subjected to first level diffusion and confused using 3D logistic map. The resultant is encoded as a DNA sequence E(n), using any one of the eight rules for encoding DNA. The DNA XOR operation is performed between E(n) and 3D logistic map DNA sequence L(n). Finally, the encrypted feature set is attained by DNA decoding. In the test phase, the proposed system decrypts the features and is matched with a stored trained model to locate the identity of the speaker. Overall accuracy is 88% for the text independent and 96% for the text dependent person authentication system tested with genuine utterances. This research is extended to estimate the performance against attacks utterance and propose system is assessed with respect to rejection rate.

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  1. Department of ECE, SASTRA Deemed to be University, Thanjavur, Tamilnadu, India

    R. Nagakrishnan & A. Revathi

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  1. R. Nagakrishnan
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R.Nagakrishnan and A. Revathi contributed to the design and implementation of the research, to the analysis of the results and to the writing of the manuscript.

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Correspondence to A. Revathi.

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Nagakrishnan, R., Revathi, A. Novel secured speech communication for person authentication. Multimed Tools Appl 82, 24771–24801 (2023). https://doi.org/10.1007/s11042-022-14246-4

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