A Survey on Intrusion Detection System in Ad Hoc Networks Based on Machine Learning

This advanced research survey aims to perform intrusion detection and routing in ad hoc networks in wireless MANET networks using machine learning techniques. The MANETs are composed of several ad-hoc nodes that are randomly or deterministically distributed for communication and acquisition and to forward the data to the gateway for enhanced communication securely. MANETs are used in many applications such as in health care for communication; in utilities such as industries to monitor equipment and detect any malfunction during regular production activity. In general, MANETs take measurements of the desired application and send this information to a gateway, whereby the user can interpret the information to achieve the desired purpose. The main importance of MANETs in intrusion detection is that they can be trained to detect intrusion and real-time attacks in the CIC-IDS 2019 dataset. MANETs routing protocols are designed to establish routes between the source and destination nodes. What these routing protocols do is that they decompose the network into more manageable pieces and provide ways of sharing information among its neighbors first and then throughout the whole network. The landscape of exciting libraries and techniques is constantly evolving, and so are the possibilities and options for experiments. Implementing the framework in python helps in reducing syntactic complexity, increases performance compared to implementations in scripting languages, and provides memory safety.