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Clustering of Network Link Characteristic for Detector Placement of Macroscopical Prewarning
Hangzhou, Zhejiang, China June 20-June 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IMSCCS.2006.1982006 First International Multi-Sympos ...
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Hui He, Harbin Institute of Technology, China
Mingzeng Hu, Harbin Institute of Technology, China
Hongli Zhang, Harbin Institute of Technology, China
Network-based and distributed intrusion detection system is aroused by the burst-outs of large-scale abnormal events. How to place detection instruments is the key to the detections. The paper turned the problem of detector placement to that of the clustering of topology graph. A novel Bidirectional Hierarchical Clustering algorithm is put forward, which decreases the amount of result clusters by integration of initial marker selection method based on node out-degree. The simulation results demonstrate that our clustering approaches effectively by comparison on the three evaluations metric, Diameter Stability, Average Advantage Ratio and Average Coefficient of Variation.
Citation:
Hui He, Mingzeng Hu, Hongli Zhang, "Clustering of Network Link Characteristic for Detector Placement of Macroscopical Prewarning," imsccs, vol. 2, pp.155-159, 2006 First International Multi-Symposiums on Computer and Computational Sciences, 2006
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