A New Method for Intrusion Detection Using Genetic Algorithm and Neural network

سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 522

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شناسه ملی سند علمی:

JR_JACET-3-4_005

تاریخ نمایه سازی: 18 تیر 1398

چکیده مقاله:

Abstract— In order to provide complete security in a computer system and to prevent intrusion, intrusion detection systems (IDS) are required to detect if an attacker crosses the firewall, antivirus, and other security devices. Data and options to deal with it. In this paper, we are trying to provide a model for combining types of attacks on public data using combined methods of genetic algorithm and neural network. The goal is to make the designed model act as a measure of system attack and combine optimization algorithms to create the ultimate accuracy and reliability for the proposed model and reduce the error rate. To do this, we used a feedback neural network, and by examining the worker, it can be argued that this research with the new approach reduces errors in the classification.with the rapid development of communication and information technology and its applications, especially in computer networks, there is a new competition in information security and network security.

نویسندگان

mohammadreza hosseinzadehmoghadam

Department of Computer Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

seyed javad mirabedini

Department of Computer Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

toraj banirostam

Department of Computer Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.