Secure Secret Sharing Enabled b-band Mini Vaults Bio-Cryptosystem for Vectorial Biometrics

Yenlung Lai, Jung Yeon Hwang, Zhe Jin, Soo Hyung Kim, Sangrae Cho, Andrew Beng Jin Beng Jin Teoh

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Biometric Cryptosystems for secret binding such as fuzzy vault and fuzzy commitment are provable secure and offers a convenient way for secret management and protection. Despite numerous practical schemes have been reported, they are deficient in resisting several security and privacy attacks. In this paper, we propose a novel bio-cryptosystem that based on the three key ingredients namely Index of Maximum (IoM) hashing, (m, k) threshold secret sharing and b-band mini vaults notion. The IoM hashing is motivated from the ranking based Locality Sensitive Hashing theory meant for non-invertible transformation. On the other hand, the (m, k) threshold secret sharing scheme and the b-band mini vaults manage overcome inherent limitations of biometric cryptosystems when integrated with IoM hashing. The proposed scheme strikes the balance between performance and the privacy/security protection. Unlike fuzzy vault and fuzzy commitment, which primarily devised for unordered and binary biometrics, respectively, our scheme is tailored for feature vector-based biometrics (vectorial biometrics). Comprehensive experiments on fingerprint vectors that derived from several FVC fingerprint benchmarks and rigorous analysis demonstrate decent secret retrieval performance yet offer strong resilience against six major security and privacy attacks

Original languageEnglish
JournalIEEE Transactions on Dependable and Secure Computing
DOIs
Publication statusAccepted/In press - 2018 Jan 1

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Biometrics
Cryptography
Experiments

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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title = "Secure Secret Sharing Enabled b-band Mini Vaults Bio-Cryptosystem for Vectorial Biometrics",
abstract = "Biometric Cryptosystems for secret binding such as fuzzy vault and fuzzy commitment are provable secure and offers a convenient way for secret management and protection. Despite numerous practical schemes have been reported, they are deficient in resisting several security and privacy attacks. In this paper, we propose a novel bio-cryptosystem that based on the three key ingredients namely Index of Maximum (IoM) hashing, (m, k) threshold secret sharing and b-band mini vaults notion. The IoM hashing is motivated from the ranking based Locality Sensitive Hashing theory meant for non-invertible transformation. On the other hand, the (m, k) threshold secret sharing scheme and the b-band mini vaults manage overcome inherent limitations of biometric cryptosystems when integrated with IoM hashing. The proposed scheme strikes the balance between performance and the privacy/security protection. Unlike fuzzy vault and fuzzy commitment, which primarily devised for unordered and binary biometrics, respectively, our scheme is tailored for feature vector-based biometrics (vectorial biometrics). Comprehensive experiments on fingerprint vectors that derived from several FVC fingerprint benchmarks and rigorous analysis demonstrate decent secret retrieval performance yet offer strong resilience against six major security and privacy attacks",
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Secure Secret Sharing Enabled b-band Mini Vaults Bio-Cryptosystem for Vectorial Biometrics. / Lai, Yenlung; Hwang, Jung Yeon; Jin, Zhe; Kim, Soo Hyung; Cho, Sangrae; Teoh, Andrew Beng Jin Beng Jin.

In: IEEE Transactions on Dependable and Secure Computing, 01.01.2018.

Research output: Contribution to journalArticle

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