TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
PCA-CIA Ensemble-based Feature Extraction for Bio-Key Generation |
| 영문제목(English Title) |
PCA-CIA Ensemble-based Feature Extraction for Bio-Key Generation |
| 저자(Author) |
Aeyoung Kim
Changda Wang
Seung-Hyun Seo
|
| 원문수록처(Citation) |
VOL 14 NO. 07 PP. 2919 ~ 2937 (2020. 07) |
한글내용
(Korean Abstract) |
|
영문내용
(English 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.
|
| 키워드(Keyword) |
Face Image-based Seed
Feature Extraction Ensemble
Bio-Key Generation
Biometric Cryptography
Multivariate Quadratic-based Post-Quantum Cryptogr
|
| 파일첨부 |
PDF 다운로드
|
