DocumentCode
3061951
Title
D-S Evidence Theory and its Data Fusion Application in Intrusion Detection
Author
Tian, Junfeng ; Zhao, Weidong ; Du, Ruizhong ; Zhang, Zhe
Author_Institution
Hebei University, Baoding, China
fYear
2005
fDate
05-08 Dec. 2005
Firstpage
115
Lastpage
119
Abstract
Based on the D-S Evidence Theory and its Data Fusion technology, a new Intrusion Detection Data Fusion Model-IDSDFM is presented. This model can merge alerts of different types of IDSs, make intelligent inference by applying the D-S Evidence Theory, and estimate the current security situation according to the fusion result. Then some IDSs in the network are dynamically adjusted to strengthen the detection of the data that relate to the attack attempt. Consequently, the false positive rate and the false negative rate are effectively reduced, and the detection efficiency of IDS is accordingly improved.
Keywords
Application software; Bayesian methods; Computer science; Data security; Estimation theory; Information security; Intrusion detection; Mathematical model; Mathematics; Switches;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel and Distributed Computing, Applications and Technologies, 2005. PDCAT 2005. Sixth International Conference on
Print_ISBN
0-7695-2405-2
Type
conf
DOI
10.1109/PDCAT.2005.109
Filename
1578878
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