Title :
A kind of improved attribute reduction algorithm in intrusion detection application research based on Rough sets theory
Author :
Lian, Chen ; Wenbing, Yang
Author_Institution :
Coll. of Inf. Eng., Nanchang Univ., Nanchang, China
Abstract :
This paper is mainly about Rough sets theory into the concrete field of intrusion detection, which based on the intrusion detection technology of Rough set. In guarantee of intrusion detection function unchanged, to deal with the object data with the attribute reduction algorithm of Rough set. It has greatly reduced the characteristics of the dimension, the information redundancy and improved the intrusion detection data extraction and intrusion detection rates by removing redundant data. It has showed that the rough set theory applied in intrusion detection is effective, and achieved good inspection rate and low by mistake examining rate through KDDCup99 data sets in the experimental results.
Keywords :
rough set theory; security of data; KDDCup99 data sets; attribute reduction algorithm improvement; data extraction; information redundancy; intrusion detection application research; object data; rough sets theory; Computers; Data mining; Inspection; Intrusion detection; Probes; Rough sets; Attribute importance rate; Attribute reduction; Intrusion detection; Rough sets;
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
DOI :
10.1109/CSAE.2011.5952602
