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

doi:10.1155/2018/6107912

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

School of Cybersecurity

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

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 language	English
Article number	6107912
Journal	Security and Communication Networks
Volume	2018
DOIs	https://doi.org/10.1155/2018/6107912
Publication status	Published - 2018

ASJC Scopus subject areas

Information Systems
Computer Networks and Communications

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title = "Construction of a New Biometric-Based Key Derivation Function and Its Application",

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.",

author = "Minhye Seo and Park, {Jong Hwan} and Youngsam Kim and Sangrae Cho and Lee, {Dong Hoon} and Hwang, {Jung Yeon}",

note = "Funding Information: This work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2016-0-00097, Development of Biometrics-Based Key Infrastructure Technology for Online Identification and No. 2018-0-01369, Developing Blockchain Identity Management System with Implicit Augmented Athentication and Privacy Protection for O2O Services.) Publisher Copyright: {\textcopyright} 2018 Minhye Seo et al.",

year = "2018",

doi = "10.1155/2018/6107912",

language = "English",

volume = "2018",

journal = "Security and Communication Networks",

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AU - Seo, Minhye

AU - Park, Jong Hwan

AU - Kim, Youngsam

AU - Cho, Sangrae

AU - Lee, Dong Hoon

AU - Hwang, Jung Yeon

N1 - Funding Information: This work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2016-0-00097, Development of Biometrics-Based Key Infrastructure Technology for Online Identification and No. 2018-0-01369, Developing Blockchain Identity Management System with Implicit Augmented Athentication and Privacy Protection for O2O Services.) Publisher Copyright: © 2018 Minhye Seo et al.

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

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

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