Deep secure PalmNet: A novel cancelable palmprint template protection scheme with deep attention net and randomized hashing security mechanism

Khan, Md Sabuj; Li, Hengjian; Zhao, Chuan

doi:10.1016/j.cose.2024.103863

Computers & Security

2024

DOI: 10.1016/j.cose.2024.103863

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Deep secure PalmNet: A novel cancelable palmprint template protection scheme with deep attention net and randomized hashing security mechanism

Md Sabuj Khan,

Hengjian Li,

Chuan Zhao

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Cited by 2 publications

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Privacy-preserving speaker verification system using Ranking-of-Element hashing

Nguyen-Le,

Tran,

Nguyen

et al. 2025

Pattern Recognition

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Privacy-preserving speaker verification system using Ranking-of-Element hashing

Nguyen-Le,

Tran,

Nguyen

et al. 2025

Pattern Recognition

View full text Add to dashboard Cite

Cancelable palmprint: intelligent framework toward secure and privacy-aware recognition system

Ali,

Elhefnawy,

Abo-Zahhad

2024

EURASIP J. on Info. Security

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Cancelable template protection techniques are indispensable to provide essential security and privacy privileges in biometric systems. This paper introduces an efficient cancelable palmprint recognition technique based on multi-level transformations. Gabor filtering with feature remapping is introduced for extracting highly discriminative features. Histogram remapping is applied to nonlinearly transform the downsampled Gabor features to be normally distributed. This feature-remapping step is proposed to enhance the discriminatory power and alleviate the effect of feature variability and image artifacts. Comb filtering is applied to the mapped features as a first protection layer. To provide security guarantees against linkability attacks, index-based locality-sensitive hashing (LSH) is introduced as a second protection layer to transform the comb-filtered mapped real-valued features into maximum-ranked indices. Recognition is performed in the secured domain to accelerate matching and to preserve the user’s privacy. Results show that the proposed scheme provides a large re-issuance ability, protects templates from being inverted, and demonstrates strong unlinkability across different databases. In addition, favorable verification/identification accuracy is obtained and the system satisfies the needs for real-time applications. A global measure $${D}_{\leftrightarrow }^{sys}$$ D ↔ sys value of 0.01 is obtained, and thus, correlation attacks are mitigated. The recognition results for the legitimate scenario are 100% identification accuracy and 0% EER. For the worst case (same token scenario), the corresponding results are 99.752% and 0.31%, respectively.

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Deep secure PalmNet: A novel cancelable palmprint template protection scheme with deep attention net and randomized hashing security mechanism

Cited by 2 publications

References 36 publications

Privacy-preserving speaker verification system using Ranking-of-Element hashing

Privacy-preserving speaker verification system using Ranking-of-Element hashing

Cancelable palmprint: intelligent framework toward secure and privacy-aware recognition system

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