Title :
Method on rule extracting in misuse intrusion detection based on rough set genetic algorithm
Author :
Qin Aiming ; Shao Li
Author_Institution :
Inf. Coll., Capital Univ. of Econ. & Bus., Beijing, China
Abstract :
An integrated method that combines rough set theory and genetic algorithm for rule Extracting is present. It takes full advantages of rough set theory and genetic algorithm. Reduction is done firstly on the basis of rough set theory that is good at processing redundant and inconsistent data. Then genetic algorithm is used to mine rules. Using such a method, simple and reasonable rules can be deduced. The operation procedure is illustrated by an example, and the results show that the algorithm is effective and feasible when applying it to misuse intrusion detection for rule acquisition.
Keywords :
data mining; genetic algorithms; rough set theory; security of data; genetic algorithm; inconsistent data; integrated method; misuse intrusion detection; operation procedure; redundant data; rule acquisition; rule extracting method; rule mining; data mining; machine learning; misuse detection; rough set genetic algorithm;
Conference_Titel :
Computing and Convergence Technology (ICCCT), 2012 7th International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-0894-6
