DocumentCode :
2894421
Title :
An Intrusion-Tolerant Intrusion Detection Method Based on Real-Time Sequence Analysis
Author :
Zhao, Feng ; Li, Qing-Hua ; Jin, Li
Author_Institution :
Sch. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan
fYear :
2006
fDate :
13-16 Aug. 2006
Firstpage :
2692
Lastpage :
2696
Abstract :
One of the most advanced research issues in network security is intrusion-tolerant intrusion detection, which has become another essential technique to protect computer systems and prevent the intrusion from generating a system failure. This paper presents a novel intrusion-tolerant intrusion detection method based on real-time sequence forecast analysis for network stream. We devise linear regression techniques to forecast network stream sequences. According to these, it´s helpful for us to analysis intruders´ behaviors and to recognize undesirable intrusions. We also provide recovery strategies to tolerate intrusion. Experiments on the http server demonstrate that our method outperform the others
Keywords :
computer networks; regression analysis; security of data; computer systems; intrusion-tolerant intrusion detection method; linear regression techniques; network security; network stream sequences; real-time sequence forecast analysis; Computer networks; Computer security; Cybernetics; Failure analysis; High performance computing; Information analysis; Intrusion detection; Machine learning; Performance analysis; Protection; Real time systems; Web server; Intrusion detection; Intrusion tolerance; Sequence Forecast; Trust recovery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
Type :
conf
DOI :
10.1109/ICMLC.2006.258927
Filename :
4028518
Link To Document :
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