Abstract
In this paper, the optimal brain surgeon (OBS) strategy is introduced to improve the iterative rule of non-negative matrix factorization (NMF) algorithm for intrusion detection, which is called OBS-NMF algorithm. A new convergence condition and criterion function are proposed to improve the performance of the OBS-NMF algorithm. Then the proposed method is applied in the HIDS and NIDS, the experimental results show that our method can obtain higher accuracy and better stability than the NMF algorithm, and achieves satisfying detection performance. The improved OBS-NMF algorithm is also suitable for real-time intrusion detection.
The corresponding author is Yue Wu (ywu@xidian.edu.cn).
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Acknowledgment
This work was supported in part by the National Basic Research Program (973 Program) of China (No. 2013CB329402), the National Natural Science Foundation of China (No. 61573015 and 61702392) and the Fundamental Research Funds for the Central Universities under Grant JBX170311.
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Ma, W., Wu, Y., Wang, S., Gong, M. (2017). Improved OBS-NMF Algorithm for Intrusion Detection. In: He, C., Mo, H., Pan, L., Zhao, Y. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2017. Communications in Computer and Information Science, vol 791. Springer, Singapore. https://doi.org/10.1007/978-981-10-7179-9_47
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DOI: https://doi.org/10.1007/978-981-10-7179-9_47
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