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SCAN-speech biometric template protection based on genus-2 hyper elliptic curve

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Abstract

Rapid growth in the mobile technology manifolds the usage of mobile devices. It leads to the development and popularity of mobile application in diversified domains like finance, commerce, and government services. Extensive services can be explored conveniently and cost-effectively from these applications using speaker recognition based authentication to determine the identity of the individuals requesting service. Speech template that is stored in these mobile devices necessitates the prime concern of preserving the private data from unauthorized access and privacy breaches. It is highly feasible to prove the authenticity of the person using speech as a biometric to ensure that the rendered services are accessed only by the legitimate user. If the speech template stored in the database for comparison is compromised, then the authentication process will become obsolete. This issue had motivated the need for highly secured, faster and lightweight model named as (SCAN) - Speech biometriC templAte protectioN system based on the genus-2 hyper elliptic curve. Mobile devices are smaller in size and often restricted by memory and power constraints. Hence it requires a cryptosystem with lesser key size offering the higher degree of security and guard against sophisticated attacks. The proposed SCAN system provides the complete solution for this challenge uniquely by designing genus-2 hyper elliptic curve cryptosystem for speech template. The elaborate analysis from the results traces ideal values for MSE, PSNR, BRT, and EUD. This ratifies the suitability of this work that craves for higher encryption and decryption reliability. It offers high resistance to various attacks as it involves HECC that comes under the category of discrete logarithmic problem. This SCAN system can also reap the benefit of light weight processing, better ERR and authentication accuracy with induced parallelism.

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Acknowledgements

This part of this research work is supported by Department of Science and Technology (DST), Science and Engineering Board (SERB), Government of India under the ECR grant (ECR/2017/000679/ES)

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Authors and Affiliations

  1. Department of CSE, School of Computing, SASTRA Deemed University, Thanjavur, TN, India

    N. Sasikaladevi, K. Geetha, N. Mahalakshmi & N. Archana

  2. Department of ECE, School of EEE SASTRA Deemed University, Thanjavur, TN, India

    A. Revathi

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  1. N. Sasikaladevi
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  2. K. Geetha
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  3. A. Revathi
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  4. N. Mahalakshmi
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Correspondence to N. Sasikaladevi.

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Sasikaladevi, N., Geetha, K., Revathi, A. et al. SCAN-speech biometric template protection based on genus-2 hyper elliptic curve. Multimed Tools Appl 78, 18339–18361 (2019). https://doi.org/10.1007/s11042-019-7208-1

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