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Transactions: WSEAS TRANSACTIONS ON SYSTEMS
Transactions ID Number: 32-836
Full Name: Guisong Liu
Position: Associate Professor
Age: ON
Sex: Male
Address: School of Computer Science and Engineering,University of Electronic Science and Technology of China
Country: CHINA
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E-mail address: guisongliu@gmail.com
Other E-mails: lgs@uestc.edu.cn
Title of the Paper: a principal components analysis neural gas algorithm for anomalies clustering
Authors as they appear in the Paper: Guisong Liu, Xiufen Fang, Tingzhu Huang
Email addresses of all the authors: guisongliu@gmail.com,Xiufenfang@gamil.com
Number of paper pages: 10
Abstract: Neural gas network is a single-layered soft competitive neural network, which can be applied to clustering analysis with fast convergent speed comparing to Self-organizing Map (SOM), K-means etc. Combining neural gas with principal component analysis, this paper proposes a new clustering method, namely principal components analysis neural gas (PCA-NG), and the online learning algorithm is also given. The soft competitive learning of PCA-NG is based on local principal subspace, which characterizes the profile of a certain cluster. We utilize the PCA-NG to the domain of intrusion detection. Some experiments are carried out to illustrate the performance of the proposed approach by using a synthetic Gaussian-distributed dataset and the KDD CUP 1999 Intrusion Detection Evaluation dataset.
Keywords: Intrusion Detection, Neural Gas Network, Principal Component Analysis, Cluster Analysis
EXTENSION of the file: .doc
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