Introducing a Two-step Strategy based on Deep Learning Enhance the Accuracy of Intrusion Detection Systems in the Network

Majlesi Journal of Telecommunication Devices

مقاله 4، دوره 8، شماره 1، خرداد 2019، صفحه 21-25   

نوع مقاله: Articles

نویسندگان

Ali Bahmani^* ؛ Amirhassan Monajemi

Islamic Azad University Isfahan

چکیده

Intrusion Detection System is one of the most important security features of modern computer networks that can detect network penetration through a series of functions. This system is independently used (e.g. Snort) or with various security equipment (such as Antivirus, UTM, etc.) on the network and detects an attack based on two techniques of abnormal detection and signature-based detection. Currently, most of the researches in the field of intrusion detection systems have been done based on abnormal behavior using a variety of methods including statistical techniques, Artificial Intelligence (AI), data mining, and machine learning. In this study, we can achieve an effective accuracy using a candidate class of the KDD dataset and deep learning techniques.

کلیدواژه‌ها

Intrusion Detection System؛ Network Security؛ deep learning

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