Towards an Effective Intrusion Detection System using Machine Learning techniques: Comprehensive Analysis and Review

Abstract

With the fast growth of network technologies, Experts in many disciplines have shown great interest in network security. Many new assaults occur and it's a challenge for network security mechanisms to detect these sophisticated incursions. Intruders get intelligent each day, consistent with the progress of safety devices. The IDS is a weapon which can prevent the network from several types of interference. IDS evaluate the status of hardware and software operations on a network for threatening players in defense of data confidentiality, integrity and availability. The usage of machine learning algorithms simplified this job for IDS. In this work, the merits and demerits of the current publications from ML-based IDS offered solutions are discussed. This study also points to several research gaps that may be utilized in order to improve and create efficientIDSs.