• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

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


Abstract

Post-Quantum Cryptography (PQC) is rapidly developing as a stable and reliable quantum-resistant form of cryptography, throughout the industry. Similarly to existing cryptography, however, it does not prevent a third-party from using the secret key when third party obtains the secret key by deception, unauthorized sharing, or unauthorized proxying. The most effective alternative to preventing such illegal use is the utilization of biometrics during the generation of the secret key. In this paper, we propose a biometric-based secret key generation scheme for multivariate quadratic signature schemes, such as Rainbow. This prevents the secret key from being used by an unauthorized third party through biometric recognition. It also generates a shorter secret key by applying Principal Component Analysis (PCA)-based Confidence Interval Analysis (CIA) as a feature extraction method. This scheme’s optimized implementation performed well at high speeds.


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Cite this article

[IEEE Style]
A. Kim, C. Wang and S. Seo, "PCA-CIA Ensemble-based Feature Extraction for Bio-Key Generation," KSII Transactions on Internet and Information Systems, vol. 14, no. 7, pp. 2919-2937, 2020. DOI: 10.3837/tiis.2020.07.011.

[ACM Style]
Aeyoung Kim, Changda Wang, and Seung-Hyun Seo. 2020. PCA-CIA Ensemble-based Feature Extraction for Bio-Key Generation. KSII Transactions on Internet and Information Systems, 14, 7, (2020), 2919-2937. DOI: 10.3837/tiis.2020.07.011.