DocumentCode :
3740372
Title :
Artificial immune system based intrusion detection
Author :
Eman Abd El Raoof Abas;Hatem Abdelkader;Arabi Keshk
Author_Institution :
Information System department, Faculty of Computer and Information, Suez Canal University, Egypt
fYear :
2015
Firstpage :
542
Lastpage :
546
Abstract :
Due to the growing of internet applications, the needs of internet security are increasing. Intrusion detection system is the primary approaches used for saving systems from internal and external intruders. Several techniques have been applied to intrusion detection system such as artificial neural Network, genetic algorithms, artificial immune system. Most researchers suggested improving the intrusion detection performance and accuracy. In this paper, we used artificial immune system network based intrusion detection. In our framework we suggest using GureKddcup database set for intrusion detection and apply R-chunk algorithm of artificial immune system technique, it is used for anomaly detection .An optimized feature selection of rough set theory used for enhancing time consuming.
Keywords :
"Immune system","Databases","Floods"
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Information Systems (ICICIS), 2015 IEEE Seventh International Conference on
Print_ISBN :
978-1-5090-1949-6
Type :
conf
DOI :
10.1109/IntelCIS.2015.7397274
Filename :
7397274
Link To Document :
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