Secure Hamming distance computation for biometrics using ideal-lattice and ring-LWE homomorphic encryption

Masaya Yasuda

研究成果: ジャーナルへの寄稿学術誌査読

16 被引用数 (Scopus)

抄録

With widespread development of biometrics, concerns about security and privacy are rapidly increasing. Homomorphic encryption enables us to operate on encrypted data without decryption, and it can be applied to construct a privacy-preserving biometric system. In this article, we apply two homomorphic encryption schemes based on ideal-lattice and ring-LWE (Learning with Errors), which both have homomorphic correctness over the ring of integers of a cyclotomic field. We compare the two schemes in applying them to privacy-preserving biometrics. In biometrics, the Hamming distance is used as a metric to compare two biometric feature vectors for authentication. We propose an efficient method for secure Hamming distance. Our method can pack a biometric feature vector into a single ciphertext, and it enables efficient computation of secure Hamming distance over our packed ciphertexts.

本文言語英語
ページ(範囲)85-103
ページ数19
ジャーナルInformation Security Journal
26
2
DOI
出版ステータス出版済み - 3月 4 2017

!!!All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • コンピュータ サイエンスの応用
  • 情報システムおよび情報管理

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