NDLI: A New Approach to Network Anomaly Attack Detection

Content Provider	IEEE Xplore Digital Library
Author	Hongyu Yang Lixia Xie Feng Xie
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. Sci., Civil Aviation Univ. of China, Tianjin (Hongyu Yang; Lixia Xie)
Abstract	This paper presents a new approach to detect attacks from network activities. Network connections were transformed into data points in the predefined feature space. The influence function was designed to quantify the influence of an object and, further, the data field was divided into positive field and negative field according to the source point's category. To perform classification, all the labeled training samples were regarded as source points and build a data field in the feature space. When detecting, the influence felt by given testing point in this field was calculated and behaviors class was judged according to the sign and magnitude of the influence. Experimental results demonstrate that the detection performance of our approach is satisfying.
Starting Page	317
Ending Page	321
File Size	377368
Page Count	5
File Format	PDF
ISBN	9780769533056
DOI	10.1109/FSKD.2008.15
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	anomaly attack Costs Machine learning algorithms Data security data field classification Information technology Computer science network intrusion detection Intrusion detection Information security Computer security Testing Fuzzy systems
Content Type	Text
Resource Type	Article

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