Abstract
In order to provide protection for biometric features in palmprint authentication, we propose a palmprint authentication scheme suitable for personal environments with privacy-preserving trait using the ElGamal encryption scheme which is mulplicatively homomorphic. To achieve faster running speed, we use binary vectors to represent palmprint features and use Hamming distance to indicate the similarity of different feature vectors. We give security and performance analysis, and use Matlab to implement some key modules of the proposed scheme. Theoretical analysis and experimental results show that the proposed scheme achieves confidential computations of palmprint feature vectors. The recognition accuracy can meet practical requirements and the overall performance transcends existing relative schemes.
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Acknowledgements
This work is partially supported by the National Natural Science Foundation of China “Research on Key Technologies of Secure Cloud Data Storage Based on (Fully) Homomorphic Encryption” (Grant No. 61772150), the Crypto Development Fund of China (Grant No. MMJJ20170217) and the open subject project “Palmprint feature protection research based on homomorphic encryption” of Guangxi Key Laboratory of cryptography and information security (Approval No. GCIS201622) and the planning fund project of ministry of education (12YJAZH136).
We thank Diongxiong WU and Zhiqiang Gao for helpful comments and discussions.
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Wang, H., Ding, Y., Tang, S., Wang, J. (2017). An Efficient Privacy-Preserving Palmprint Authentication Scheme Based on Homomorphic Encryption. In: Wen, S., Wu, W., Castiglione, A. (eds) Cyberspace Safety and Security. CSS 2017. Lecture Notes in Computer Science(), vol 10581. Springer, Cham. https://doi.org/10.1007/978-3-319-69471-9_39
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DOI: https://doi.org/10.1007/978-3-319-69471-9_39
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