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.

A Face-Authentication Based Searchable Encryption Scheme For Mobile Device

“…As shown in Figure 6(a), our solution can achieve an accuracy of 92.3%. Other schemes [18][19][20] calculate the templates in unencrypted form, indicating that the accuracy of template recognition does not significantly decrease after encryption in our scheme. Additionally, we have implemented our FBKDF on encrypted biometric templates and have presented the results in Figure 6(b).…”

“…The mean and variance of the ith feature are calculated as: • P rocess(f eature vector) → (w 0 ): Quantize feature vector value and transform it into a highly distinguishable binary string(w 0 ). Feature vector quantization approach can be seen in [17][18][19]. In this work,w 0 is calculated as…”

PCA-CIA Ensemble-based Feature Extraction for Bio-Key Generation

“…It is not easy to find a representative study because their proposals do not provide a reasonable and concrete method [18][19][20][21]. Minhye Seo et al proposed a new biometric-based key derivation function for enhancement of the authentication system by the replacement of password-based key derivation functions [22]. Some researchers have tried to use other noise sources such as Physical Unclonable Function and image link, but these results are also insignificant [23].…”