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학술지 Feature Construction Scheme for Efficient Intrusion Detection System
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저자
김은혜, 이승민, 권기훈, 김세현
발행일
201003
출처
Journal of Information Science and Engineering, v.26 no.2, pp.527-547
ISSN
1016-2364
출판사
Academia Sinica
협약과제
10MC1100, 실시간 우편물류 운영기술 개발, 박종흥
초록
For computationally efficient and effective IDS, it is essential to identify important input features. In this paper, a statistical feature construction scheme is proposed in which factor analysis is orthogonally combined with an optimized k-means clustering technique. As a core component for unsupervised anomaly detection, the proposed feature construction scheme is able to exclude the redundancy of features optimally via the consideration of the similarity of feature responses through a clustering analysis based on the feature space reduced in a factor analysis. The performance of the proposed method was evaluated using different data sets reduced by the ranking of the importance of input features. Experimental results show a significant detection rate through a good subset of features deemed to be critical to the improvement of the performance of classifiers.
키워드
Factor analysis, Feature construction, Intrusion detection, K-means clustering, Self organizing map
KSP 제안 키워드
Clustering Analysis, Computationally Efficient, Construction Scheme, Data sets, Factor Analysis, Feature space, Input features, Intrusion detection system(IDS), K-means clustering technique, Self-organizing Map, Statistical Features