Title :
A Fast Fuzzy Set Intrusion Detection Model
Author :
Lin Jianhui ; Huang Tianshu ; Bingjie, Zhao
Author_Institution :
Sch. of Electron. Inf., Wuhan Univ., Wuhan
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;
Conference_Titel :
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3488-6
DOI :
10.1109/KAM.2008.21