TY  - JOUR
T1  - A New Method for Detecting Network Intrusion by Using a Combination of
Genetic Algorithm and Support Vector Machine Classifier
AU - Jahromy, Behrooz Mabadi AU - Honarvar, Ali Reza AU - Saif, Mojtaba AU - Jahromy, Mohammad Ali Mabadi 
JO  - Journal of Engineering and Applied Sciences
VL  - 11
IS  - 4
SP  - 810
EP  - 815
PY  - 2016
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2016.810.815
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2016.810.815
KW  - Computer networks
KW  -intrusion detection
KW  -machine learning
KW  -genetic algorithms
KW  -support vector machine
AB  - The purpose of intrusion detection is to identify an unauthorized use, misuse and damage to computer systems and networks by either of two internal users and external attackers. In this study, we have presented a new approach based on machine learning techniques to identify malicious attacks and provide security at an accessible level for users. The introduced method uses a genetic algorithm with a statistical target function based on the data distribution to select the features and the support vector machine for classification. The results of the simulation proposed good quality of the indicative method.
ER  -