본문 바로가기
KERD
논문KCI 등재

HV-KEM을 이용한 생체 정보 기반 인증 프로토콜

Biometric Authentication Protocol Using Hidden Vector Key Encapsulation Mechanism

1

조회

0

다운로드

1

인용

0

참고문헌

키워드

주제분류컴퓨터학

초록

생체 정보를 이용한 사용자 인증은 사용자가 어떠한 정보도 소유하거나 기억할 필요가 없으므로 사용자 측면에서매우 편리하다. 그러나 생체 정보는 한번 노출되면 영구적으로 사용할 수 없기 때문에 인증 수행 시 생체 정보의 프라이버시 보호가 필수적이다. 또한 생체 정보는 본질적으로 노이즈가 있기 때문에 인증 수행 시 적절한 오차 범위이내에서 이를 처리할 수 있어야 한다. 최근 퍼지 추출기(fuzzy extractor)를 이용한 생체 정보 기반 인증 프로토콜에 대한 연구가 활발히 진행되고 있으나, 사용자가 헬퍼 데이터(helper data)를 추가적으로 기억해야 하는 문제점이 존재한다. 본 논문에서는 함수 암호 중 하나인 HV-KEM(Hidden Vector Key Encapsulation Mechanism)을 이용하여 사용자가 어떠한 정보도 소유하거나 기억할 필요 없는 생체 정보 기반 인증 프로토콜을제안한다. 또한, 인증 프로토콜 설계를 위한 HV-KEM의 보안 요구사항을 정립하고 제안하는 인증 프로토콜을 정확성/안전성/효율성 측면에서 분석한다.

Abstract

Biometric authentication is considered as being an efficient authentication method, since a user is not required to possess or memorize any other information other than biometrics. However, since biometric information is sensitive and could be permanently unavailable in case of revealing that information just once, it is essential to preserve privacy of biometrics. In addition, since noise is inherent in the user of biometric recognition technologies, the biometric authentication needs to handle the noise. Recently, biometric authentication protocols using fuzzy extractor have been actively researched, but the fuzzy extractor-based authentication has a problem that a user should memorize an additional information, called helper data, to deal with their noisy biometric information. In this paper, we propose a novel biometric authentication protocol using Hidden Vector Key Encapsulation Mechanism(HV-KEM) which is one of functional encryption schemes. A primary advantage of our protocol is that a user does not need to possess or memorize any additional information. We propose security requirements of HV-KEM necessary for constructing biometric authentication protocols, and analyze our proposed protocol in terms of correctness, security, and efficiency.

참고문헌 (14)

  1. M. Abdalla, "“Interactive Diffie-Hellman assumptions with applications to password-based authentication,”Proc. of the Financial Cryptography", LNCS, 3570, pp.341~356 (2005)
  2. M.R. Thompson, "Certificate-based authorization policy in a PKI environment", ACM Transactions on Information and System Security, 6(4), pp.566~588 (2003)
  3. T.-C. Yeh, "A secure one-time password authentication scheme using smart cards", IEICE Transactions on Communications, E85-B(11), pp.2515~2518 (2002)
  4. G.M. Ezovski, "The electronic passport and the future of government-issued RFID-based identification", IEEE International Conference on RFID, pp.15~22 (2007)
  5. "Apple pay contactless secure payment an d tokenisation"[URL]
  6. "PalmSecure"[URL]
  7. Y. Dodis, "“Fuzzy extractor: how to generate strong keys from biometrics and other noisy data,”Advances in Cryptology, EUROCRYPT’04", LNCS, 3027, pp.523~540 (2004)
  8. Y. Dodis, "“Robust fuzzy extractors and authenticated key agreement from close secrets,” Advances in Cryptology, CRYPTO’06", LNCS, 4117, pp.232~250 (2004)
  9. A. Arakala, "“Fuzzy extractors for minutiae-based fingerprint authentication,” Advances in Biometrics, ICB’07", LNCS, 4642, pp.760~769 (2007)
  10. Q. Li, "Fuzzy extractors for asymmetric biometric representations", IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp.1~6 (2008)
  11. D. Boneh, "Functional encryption: definitions and challenges", Proceedings of the 8th Theory of Cryptography Conference, pp.253~273 (2011)
  12. J.H. Park, "Efficient hidden vector encryption for conjunctive queries on encrypted data", IEEE Transactions on Knowledge and Data Engineering, 23(10), pp.1483~1497 (2011)
  13. C. Lee, "Cancelable fingerprint templates using minutiae-based bit-strings", Journal of Network and Computer Applications, 33(3), pp.236~246 (2010)
  14. C. Chen, "Extracting biometric binary strings with minimal area under the FRR curve for the hamming distance classifier", Signal Processing, 91(4), pp.906~918 (2011)

관련 논문AI추천

이 간행물의 다른 논문 (23건)