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효율적인 LWE 기반 재사용 가능한 퍼지 추출기

An Efficient LWE-Based Reusable Fuzzy Extractor

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참고문헌

키워드

주제분류컴퓨터학

초록

퍼지 추출기는 노이즈가 섞여 입력값이 항상 같지 않은 생체 데이터로 키를 생성하여 생체 정보 노출 없이 안전하게 인증을 수행하는 바이오-암호화 기술이다. 그러나 한 사용자가 생체 데이터를 여러 서버에 등록할 경우 퍼지 추출기의 인증 과정에서 키를 올바르게 추출하기 위해 공개되는 정보인 보조 데이터에 대한 다양한 공격으로 키가 노출될 수 있다. 따라서 여러 서버에 같은 사람의 생체 데이터를 등록해도 안전한 재사용 가능한 퍼지 추출기에 관한 연구가 많이 이루어지고 있으나, 현재까지 제시된 연구들은 키 길이가 늘어남에 따라 키를 복구하는 과정의 횟수가 점진적으로 증가하여 효율적이지 않고 보안성 높은 시스템에 적용하기 힘들다. 이에 본 논문에서는 키 길이가 늘어나도 인증 과정의 수행 횟수가 같거나 비슷한 LWE 기반의 효율적이고 재사용 가능한 퍼지 추출기를 설계하였고, 제안 기법이 Apon et al.[5]이 정의한 재사용의 안전성을 만족함을 보였다.

Abstract

Fuzzy extractor is a biometric encryption that generates keys from biometric data where input values are not always the same due to the noisy data, and performs authentication securely without exposing biometric information. However, if a user registers biometric data on multiple servers, various attacks on helper data which is a public information used to extract keys during the authentication process of the fuzzy extractor can expose the keys. Therefore many studies have been conducted on reusable fuzzy extractors that are secure to register biometric data of the same person on multiple servers. But as the key length increases, the studies presented so far have gradually increased the number of key recovery processes, making it inefficient and difficult to utilize in security systems. In this paper, we design an efficient and reusable fuzzy extractor based on LWE with the same or similar number of times of the authentication process even if the key length is increased, and show that the proposed algorithm is reusably-secure defined by Apon et al.[5].

참고문헌 (18)

  1. M. Zhang, "Multibiometric Based Secure Encryption, Authentication Scheme with Fuzzy Extractor", International Journal of Network Security, 12(2), pp.50~57 (2011)
  2. N. Li, "Fuzzy extractors for biometric identication", 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), pp.667~677 (2017)
  3. X. Boyen, "Reusable cryptographic fuzzy extractors", Proceedings of the 11th ACM conference on Computer and Communications Security, pp.82~91 (2004)
  4. R. Canetti, "Reusable fuzzy extractors for low-entropy distributions", Annual International Conference on the Theory and Applications of Cryptographic Techniques, pp.117~146 (2016)
  5. D. Apon, "Efficient, reusable fuzzy extractors from LWE", International Conference on Cyber Security Cryptography and Machine Learning, pp.1~18 (2017), Springer
  6. Y. Wen, "Reusable fuzzy extractor from the decisional Diffie-Hellman assumption", Designs, Codes and Cryptography, 86(11), pp.2495~2512 (2018)
  7. Y. Wen, "Robustly reusable fuzzy extractor from standard assumptions", International Conference on the Theory and Application of Cryptology and Information Security, pp.459~489 (2018), Springer
  8. Y. Dodis, "Fuzzy extractors : How to generate strong keys from biometrics and other noisy data", International conference on the theory and applications of cryptographic techniques, pp.523~540 (2004), Springer
  9. M. Blanton, "On the(non-)reusability of fuzzy sketches and extractors and security in the computational setting", Proceedings of the International Conference on Security and Cryptography, pp.68~77 (2011)
  10. B. Fuller, "Computational fuzzy extractors", Information and computation, 275, pp.104602~ (2020)
  11. C. Peikert, "Lattice cryptography for the internet", International workshop on post-quantum cryptography, 8772, pp.197~219 (2014), Springer
  12. O. Regev, "On lattices, learning with errors, random linear codes, and cryptography", Journal of the ACM(JACM), 56(6), pp.1~40 (2009)
  13. Z. Brakerski, "Efficient fully homomorphic encryption from(standard)LWE", SIAM Journal on computing, 43(2), pp.831~871 (2014)
  14. Z. Brakerski, "Lattice-based FHE as secure as PKE", Proceedings of the 5th conference on Innovations in theoretical computer science, pp.1~12 (2014)
  15. C. Gentry, "Trapdoors for hard lattices and new cryptographic constructions", Proceedings of the fortieth annual ACM symposium on Theory of computing, pp.197~206 (2008)
  16. S. Agrawal, "Efficient lattice(H)IBE in the standard model", Annual International Conference on the Theory and Applications of Cryptographic Techniques, pp.553~572 (2010), Springer
  17. B. Barak, "Leftover hash lemma, revisited", Annual Cryptology Conference, pp.1~20 (2011), Springer
  18. S. Goldwasser, "Robustness of the learning with errors assumption", Proceedings of the Innovations in Computer Science, pp.230~240 (2010)

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