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A Model to Improve the Performance of Intrusion Detection System Based on the Genetic Algorithm

عنوان مقاله: A Model to Improve the Performance of Intrusion Detection System Based on the Genetic Algorithm
شناسه ملی مقاله: ICIETCONF01_015
منتشر شده در کنفرانس بین المللی پیشرفت های اخیر در علوم اطلاعات،مهندسی و فناوری در سال 1398
مشخصات نویسندگان مقاله:

Mohammad Hossein Gheisizadeh - Department of Information and technology Management, Islamic Azad University, Qazvin, Iran
Habib Rostami - Deepartment of Computer Engineering, Persian Gulf University , Bushehr, ۷۵۱۶۹, Iran
Gholamreza Ahmadi - Deepartment of Computer Engineering, Persian Gulf University , Bushehr, ۷۵۱۶۹, Iran

خلاصه مقاله:
According to growing ICT and human dependence on it, maintaining availability, integrity and confidentiality of information is so critical. So in this context we must protect data and networks from attacks and illegal influences. Therefore intrusion detection systems have become one of the most important issues and investigations to improve its ability, speed and flexibility in the face of Zero day s cyber-attacks. In this paper, after introducing the computer network attacks and going over the genetic algorithm, a model will be presented based on the genetic algorithm and by using inheritance features to detect the Zero day intrusions or converted types of the existing attacks(infiltration ways), and implemented it on WEKA software. Finally examine the relevant index of proposed model.

کلمات کلیدی:
Intrusion Detection System, Genetic Algorithm, Network attack, data mining

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/905360/