The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 32-602
Full Name: Wang Dawei
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: No.258 mail box, 52# Xuefu Road Nangang district, Harbin, Heilongjiang province
Country: CHINA
Tel: 15904612835
Tel prefix: +86
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E-mail address: stonetools2008@gmail.com
Other E-mails: stonetools1982@yahoo.com.cn
Title of the Paper: evolve boundary detector for anomaly detection
Authors as they appear in the Paper: Wang Dawei,Zhang Fengbin,Xi Liang
Email addresses of all the authors: stonetools2008@gmail.com,zhangfb@hrbust.edu.cn,xljyp@yahoo.com.cn
Number of paper pages: 11
Abstract: In real-valued negative selection algorithm, the variability of self sample would result in the holes on the boundary and deceiving anomalies hidden in the self region. This paper proposes a method of evolving boundary detectors to solve these problems. This new method uses evolutionary search to generate an aggressive detectors which are allowed to cover a part of self region. The aggressiveness controlled by boundary threshold can convert some volume of self sample into the fitness of boundary detector, which makes them enable to eliminate the holes on the boundary and have an opportunity to detect the deceiving anomalies hidden in the self region. Experiments are carried out using 2-dimensional dataset and real world dataset. The former was designed to demonstrate intuitively that boundary detectors can cover the holes on the boundary, while the latter was to show boundary detectors can detect the deceiving anomalies.
Keywords: Artificial Immune Systems,Anomaly Detection,Real-valued Negative Selection,Evolutionary Search,Holes,Deceiving Anomaly
EXTENSION of the file: .doc
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