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将密码学与 EEG 生物识别技术相结合。

Combining Cryptography with EEG Biometrics.

机构信息

Department of Software Engineering, Kaunas University of Technology, Studentų 50-415, Kaunas, Lithuania.

Centre of Real Time Computer Systems, Kaunas University of Technology, K. Baršausko 59-A338, Kaunas, Lithuania.

出版信息

Comput Intell Neurosci. 2018 May 22;2018:1867548. doi: 10.1155/2018/1867548. eCollection 2018.

DOI:10.1155/2018/1867548
PMID:29951089
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5987295/
Abstract

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

摘要

加密框架依赖于密钥共享来确保数据的安全性。虽然加密框架中的密钥必须能够正确复制，并且不能与用户的身份明确关联，但在生物识别框架中情况则有所不同。将密码技术与生物识别技术相结合可以解决这些问题。我们提出了一种基于离散对数问题和 Bose-Chaudhuri-Hocquenghem (BCH) 码的生物特征认证方法，对其进行了安全性分析，并展示了其安全性特征。我们使用从 42 名受试者采集的脑电图 (EEG) 数据的自有数据集来评估生物特征密码系统。实验结果表明，所描述的生物特征用户认证系统是有效的，其等错误率 (ERR) 达到 0.024。

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