모바일 환경에서 Haar-Like Features와 PCA를 이용한 실시간 얼굴 인증 시스템

• Published in: (사)디지털산업정보학회 논문지, 6(2) Vol. 6; no. 2; pp. 199 - 207
• Main Authors: 김정철, 허범근, 신나라, 홍기천, Kim, Jung Chul, Heo, Bum Geun, Shin, Na Ra, Hong, Ki Cheon
• Format: Journal Article
• Language: Korean
• Published: (사)디지털산업정보학회 01.06.2010
• Subjects: 컴퓨터학; Intrusion Detection; Data Mining; SVM; Classification; Fault Tolerance System
• ISSN: 1738-6667; 2713-9018

Recently, large amount of information in IDS(Intrusion Detection System) can be un manageable and also be mixed with false prediction error. In this paper, we propose a data mining methodology for IDS, which contains uncertainty based on training process and post-processing analysis additionally. Our system is trained to classify the existing attack for misuse detection, to detect the new attack pattern for anomaly detection, and to define border patter between attack and normal pattern. In experimental results show that our approach improve the performance against existing attacks and new attacks, from 0.62 to 0.84 about 35%.