Construction of a New Biometric-Based Key Derivation Function and Its Application

Minhye Seo, Jong Hwan Park, Youngsam Kim, Sangrae Cho, Dong Hoon Lee, Jung Yeon Hwang

Research output: Contribution to journalArticle

Abstract

Biometric data is user-identifiable and therefore methods to use biometrics for authentication have been widely researched. Biometric cryptosystems allow for a user to derive a cryptographic key from noisy biometric data and perform a cryptographic task for authentication or encryption. The fuzzy extractor is known as a prominent biometric cryptosystem. However, the fuzzy extractor has a drawback in that a user is required to store user-specific helper data or receive it online from the server with additional trusted channel, to derive a correct key. In this paper, we present a new biometric-based key derivation function (BB-KDF) to address the issues. In our BB-KDF, users are able to derive cryptographic keys solely from their own biometric data: users do not need any other user-specific helper information. We introduce a security model for the BB-KDF. We then construct the BB-KDF and prove its security in our security model. We then propose an authentication protocol based on the BB-KDF. Finally, we give experimental results to analyze the performance of the BB-KDF. We show that our proposed BB-KDF is computationally efficient and can be deployed on many different kinds of devices.

Original languageEnglish
Article number6107912
JournalSecurity and Communication Networks
Volume2018
DOIs
Publication statusPublished - 2018 Jan 1

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications

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