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• W3216185273 abstract "Biometric matching involves storing and processing sensitive user information. Maintaining the privacy of this data is thus a major challenge, and homomorphic encryption offers a possible solution. We propose a privacy-preserving biometrics-based authentication protocol based on fully homomorphic en-cryption, where the biometric sample for a user is gathered by a local device but matched against a biometric template by a remote server operating solely on encrypted data. The design ensures that 1) the user's sensitive biometric data remains private, and 2) the user and client device are securely authenticated to the server. A proof-of-concept implementation building on the TFHE library is also presented, which includes the underlying basic operations needed to execute the biometric matching. Performance results from the implementation show how complex it is to make FHE practical in this context, but it appears that, with implementation optimisations and improvements, the protocol could be used for real-world applications." @default.
• W3216185273 created "2021-12-06" @default.
• W3216185273 creator A5037461946 @default.
• W3216185273 creator A5063477888 @default.
• W3216185273 date "2021-10-01" @default.
• W3216185273 modified "2023-10-14" @default.
• W3216185273 title "Privacy-Preserving Biometric Matching Using Homomorphic Encryption" @default.
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• W3216185273 doi "https://doi.org/10.1109/trustcom53373.2021.00079" @default.
• W3216185273 hasPublicationYear "2021" @default.
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