원문정보
보안공학연구지원센터(IJSIA)
International Journal of Security and Its Applications
Vol.9 No.9
2015.09
pp.321-336
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Intrusion detection is an important way to ensure the security of computers and networks. In this paper, a new intrusion detection system (IDS) is proposed based on Hidden Conditional Random Fields (HCRFs). In order to optimize the performance of HCRFs, we bring forward the Two-stage Feature Selection method, which contains Manual Feature Selection method and Backward Feature Elimination Wrapper (BFEW) method. The BFEW is a feature selection method which is introduced based on wrapper approach. Experimental results on KDD99 dataset show that the proposed IDS not only has a great advantage in detection efficiency but also has a higher accuracy when compared with other well-known methods.
목차
Abstract
1. Introduction
2. Related Works
3. Hidden Conditional Random Fields for Intrusion Detection
4. Two-stage Feature Selection
4.1. Manual Feature Selection
4.2. Backward Feature Elimination Wrapper
5. Framework of the IDS
6. Experiments and Results
6.1. Feature Selection with BFEW
6.2. Detection Models Building for Each Layer
6.3. The Overall IDS Performance
6.4. Comparison with Other IDSs
7. Conclusion and Future Works
Acknowledgments
References
1. Introduction
2. Related Works
3. Hidden Conditional Random Fields for Intrusion Detection
4. Two-stage Feature Selection
4.1. Manual Feature Selection
4.2. Backward Feature Elimination Wrapper
5. Framework of the IDS
6. Experiments and Results
6.1. Feature Selection with BFEW
6.2. Detection Models Building for Each Layer
6.3. The Overall IDS Performance
6.4. Comparison with Other IDSs
7. Conclusion and Future Works
Acknowledgments
References
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저자정보
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