DocumentCode
2986528
Title
Improved Genetic Algorithm in Intrusion Detection Model Based on Artificial Immune Theory
Author
Jing Xiaopei ; Wang Houxiang ; Han Ruofei ; Li Juan
Author_Institution
Inf. & Electr. Coll., Naval Univ. of Eng., Wuhan, China
fYear
2009
fDate
18-20 Jan. 2009
Firstpage
1
Lastpage
4
Abstract
After analysis the characteristics of AlS-based intrusion detection system, a new AlS-based intrusion detection model based improved genetic algorithm is established. By utilizing prominent characteristics of genetic algorithm, such as automatic optimizing, global researching, and adaptability, the new model uses genetic operator to improve the candidate detectors generating algorithm and reduce detectors redundancy. The detectors generated by new model have good fitness and better detection ability. Experiments show that this model can effectively increase the true positive rate of the IDS.
Keywords
artificial immune systems; genetic algorithms; security of data; AlS-based intrusion detection system; artificial immune theory; genetic operator; improved genetic algorithm; intrusion detection model; Detectors; Educational institutions; Flowcharts; Genetic algorithms; Genetic engineering; Genetic mutations; Immune system; Information analysis; Intrusion detection; Random number generation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5272-9
Type
conf
DOI
10.1109/CNMT.2009.5374541
Filename
5374541
Link To Document