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
Link To Document :
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