Behrooz Mabadi  Jahromy, Ali Reza  Honarvar, Mojtaba  Saif, Mohammad Ali Mabadi  Jahromy, 
    A New Method for Detecting Network Intrusion by Using a Combination of
Genetic Algorithm and Support Vector Machine Classifier,
    Journal of Engineering and Applied Sciences,
    Volume 11,Issue 4,
    2016,
    Pages 810-815,
    ISSN 1816-949x,
    jeasci.2016.810.815,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2016.810.815)
    Abstract: 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.
    Keywords: Computer networks;intrusion detection;machine learning;genetic algorithms;support vector machine