Title :
Research on Method of Network Abnormal Detection Based on Hurst Parameter Estimation
Author :
Xia, Hongbin ; Xu, Wenbo
Author_Institution :
Sch. of Inf. Eng., JiangNan Univ., WuXi
Abstract :
Most researches regard the real traffic has self-similarity, so traditional model based Possion or Markov canpsilat adapt to the real traffic. In this paper, the authors use the estimation based to Hurst parameter to detect Dos attack to research on the affect of Hurst parameter change brought by DoS attack. By analyzing the 1998 DARPA Intrusion Detection Evaluation dataset, it is verify that this method can detect DoS attack, and is more reliable on the recognition of all kinds of DoS attack than any other method based on measure precision.
Keywords :
computer networks; parameter estimation; security of data; telecommunication traffic; 1998 DARPA Intrusion Detection Evaluation dataset; Dos attack detection; Hurst parameter estimation; Markov; network abnormal detection; Backscatter; Computer crime; Computer science; Internet; Intrusion detection; Parameter estimation; Software engineering; Telecommunication traffic; Traffic control; Wide area networks; Denial of Service attack; Hurst parameter; abnormal detection; network traffic; self-similarity;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.1069