Paper 2023/721

A Fast RLWE-Based IPFE Library and its Application to Privacy-Preserving Biometric Authentication

Supriya Adhikary, Indian Institute of Technology Kanpur
Angshuman Karmakar, Indian Institute of Technology Kanpur
Abstract

With the increased use of data and communication through the internet and the abundant misuse of personal data by many organizations, people are more sensitive about their privacy. Privacy-preserving computation is becoming increasingly important in this era. Functional encryption allows a user to evaluate a function on encrypted data without revealing sensitive information. Most implementations of functional encryption schemes are too time-consuming for practical use. Mera et al. first proposed an inner product functional encryption scheme based on ring learning with errors to improve efficiency. In this work, we optimize the implementation of their work and propose a fast inner product functional encryption library. Specifically, we identify the main performance bottleneck, which is the number theoretic transformation based polynomial multiplication used in the scheme. We also identify the micro and macro level parallel components of the scheme and propose novel techniques to improve the efficiency using $\textit{open multi-processing}$ and $\textit{advanced vector extensions 2}$ vector processor. Compared to the original implementation, our optimization methods translate to $89.72\%$, $83.06\%$, $59.30\%$, and $53.80\%$ improvements in the $\textbf{Setup}$, $\textbf{Encrypt}$, $\textbf{KeyGen}$, and $\textbf{Decrypt}$ operations respectively, in the scheme for standard security level. Designing privacy-preserving applications using functional encryption is ongoing research. Therefore, as an additional contribution to this work, we design a privacy-preserving biometric authentication scheme using inner product functional encryption primitives.

Metadata
Available format(s)
PDF
Category
Public-key cryptography
Publication info
Published elsewhere. IEEE Transactions on Emerging Topics in Computing
DOI
10.1109/TETC.2023.3268003
Keywords
Inner product functional encryptionOpenMPAVX2NTTPrivacy-preserving computationBiometric authentication
Contact author(s)
adhikarys @ cse iitk ac in
angshuman @ cse iitk ac in
History
2023-05-22: revised
2023-05-19: received
See all versions
Short URL
https://ia.cr/2023/721
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2023/721,
      author = {Supriya Adhikary and Angshuman Karmakar},
      title = {A Fast {RLWE}-Based {IPFE} Library and its Application to Privacy-Preserving Biometric Authentication},
      howpublished = {Cryptology {ePrint} Archive, Paper 2023/721},
      year = {2023},
      doi = {10.1109/TETC.2023.3268003},
      url = {https://eprint.iacr.org/2023/721}
}
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