NDLI: Immunity-Based Detection for Large-Scale Behavior of Denial of Service

Content Provider	IEEE Xplore Digital Library
Author	Yan Zhang Caiming Liu Zhonghua Li Hongying Qin Qin Li Jinquan Zeng
Copyright Year	2015
Description	Author affiliation: Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China (Jinquan Zeng) \|\| Sch. of Comput. Sci., Leshan Normal Univ., Leshan, China (Yan Zhang; Caiming Liu; Zhonghua Li; Hongying Qin; Qin Li)
Abstract	The network traffics of Denial of Service (DoS) rise in large scale. Adaptive detection technologies for large-scale DoS network behaviors are needed urgently. For the above, a detection method for large-scale DoS behaviors based on Artificial Immune System is proposed in this paper. The feature collection technology is used to efficiently capture large-scale network data. Network features are analyzed to form network behaviors. Network behavior elements are defined as antigens which are classified into self antigens and non-self antigens. Simple matching coefficient is used to realize the match method between antigens. Detectors are defined to simulate the evolution mechanism of AIS. The recognition mechanism in single detection node and the distributed detection mechanism are realized.
Starting Page	437
Ending Page	440
File Size	474187
Page Count	4
File Format	PDF
e-ISBN	9781467386609
DOI	10.1109/CIS.2015.111
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computers Behavior Detection Denial of Service Large-scale Network Behavior Detectors Network Attack Feature extraction Artificial Immune System Internet Computer crime Immune system
Content Type	Text
Resource Type	Article

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