Indexed by:期刊论文
Date of Publication:2012-02-01
Journal:Journal of Convergence Information Technology
Included Journals:EI、Scopus
Volume:7
Issue:3
Page Number:84-90
ISSN No.:19759320
Abstract:Network attack detection is an important aspect in maintaining a stable network. It is usually done by a rule-based method, such as firewall technology. In the case of network data stream, rule-based method cannot be changed with the help of the outside data dynamic environment. In this paper, we proposed an incremental learning method based on support vector machine (SVM), which can improve the classification accuracy as well as reduce the time-consuming aspect. The validation of our method compares with two other models: k-nearest neighbor algorithm (KNN) and decision tree. The experimental results show the robustness of the proposed model.
Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Gender:Male
Alma Mater:Dalian University of Technology
Degree:Doctoral Degree
School/Department:Dalian University of Technology
Discipline:Computer Applied Technology
Business Address:816 Yanjiao Building, Dalian University of Technology
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