Introducing a Two-step Strategy based on Deep Learning Enhance the Accuracy of Intrusion Detection Systems in the Network
الموضوعات : Majlesi Journal of Telecommunication Devices
Ali Bahmani
1
(Islamic Azad University Isfahan)
Amirhassan Monajemi
2
()
الکلمات المفتاحية: Intrusion Detection System, deep learning, Network Security,
ملخص المقالة :
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.
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