A Review on Deep Learning Method for Intrusion Detection in Network Security
Supriya Shende, Samrat Subodh Thorat · 2020
In recent past, the evolution of enormous communication and many internet applications are run on the top of internet by considering cyber security as the important parameter. Gradually intruders determine new attack types and therefore to stop attacks are remaining as a main and major concern. Intrusion detection system (IDS) can either be a device or software helps to detect and monitor the network, system or device. This helps to detect malicious, suspicious activity or policy violation and send an alert to admin. Recently, deep learning, a subset of machine learning is related with algorithms that are based on the structure and function of brain is called artificial neural networks. The development in such learning algorithms may improve the functionality of intrusion detection (ID) in the network security. The proposed method implements an effective and enhanced ID for network security by using deep learning method with KDD dataset.