DocumentCode
2126793
Title
A Fast Fuzzy Set Intrusion Detection Model
Author
Lin Jianhui ; Huang Tianshu ; Bingjie, Zhao
Author_Institution
Sch. of Electron. Inf., Wuhan Univ., Wuhan
fYear
2008
fDate
21-22 Dec. 2008
Firstpage
601
Lastpage
605
Abstract
Applying the basic fuzzy theory and method into intrusion detection has achieved a series success. In this paper, an intrusion detection model base on fuzzy sets is presented to avoid the sharp boundary problem in rules mining. Considering Apriori algorithm is time-consuming as well as space-consuming; moreover, we propose a new rule mining algorithm base prefix tree (PTBA). PTBA algorithm compress the fuzzy pattern candidate set and frequent set through constructing a tree structure, thus it can save the memory cost of fuzzy pattern candidate and frequent set. Experiments prove that capability and efficiency of IDS model is obviously improved.
Keywords
data mining; fuzzy set theory; security of data; trees (mathematics); PTBA algorithm; apriori algorithm; frequent set; fuzzy pattern candidate set; fuzzy set intrusion detection model; fuzzy theory; prefix tree; rule mining algorithm; rules mining; sharp boundary problem; Data mining; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Information technology; Intrusion detection; Knowledge acquisition; Knowledge engineering; Logistics; Training data; IDS; fuzzy set; prefix tree;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3488-6
Type
conf
DOI
10.1109/KAM.2008.21
Filename
4732897
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