NDLI: Immunity-Based Dynamic Anomaly Detection Method

Content Provider	IEEE Xplore Digital Library
Author	Feixian Sun Qiusheng Zheng Feixian Sun Tao Li
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. Sci., Zhongyuan Univ. of Technol., Zhengzhou (Feixian Sun; Qiusheng Zheng)
Abstract	In many of actual anomaly detection systems, the training data is only partially composed by the normal elements; simultaneously, self and non-self space often vary over time, so these systems often build profiles based on some of self elements and adjust themselves to adapt network varieties. However, these techniques need a large number of self elements to build the profile and lack adaptability. Aiming at the problems of traditional techniques, an immunity-based dynamic method for network anomaly detection, referred to as WAD, is proposed in this paper. WAD builds an appropriate profile using only a subset of normal elements and adapts the varieties of self and non-self space, which adjust adaptively the self radius, the detection radius, and numbers of detectors to amend the built profile. The experiment results show that WAD is an efficient solution to anomaly detection, and has the features of high detection rate, low false alarm rate, self-learning, and adaptation.
Starting Page	644
Ending Page	647
File Size	232068
Page Count	4
File Format	PDF
ISBN	9781424417476
DOI	10.1109/ICBBE.2008.157
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Computer vision Space technology Training data Detectors Biology Computational Intelligence Society Sun Computer security Immune system
Content Type	Text
Resource Type	Article

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