A distributed intelligent agent based intrusion detection system using deep learning algorithms

Abstract

Intrusion detection system (IDS) is one of the best solutions protecting against the attacks and anomalies. Behaviour based IDS is one type of IDS that is the most subject draining the interest of most research works in the cyber-security field. The main problems treated are accuracy and false positive rate. Distribution of the detection process is one solution for those problems. The distribution consists of implementing an agent based IDS where each and every agent has a goal to achieve so the intrusion detection process can be completed with the best results through the multi agent system features including the communication, negotiation, ... . The adapted solution in our model proposed is a distributed Intelligent agent based intrusion detection system using convolutional and recurrent neural networks for the training and attack prevention.