Comprehensive Review Next-Generation Intrusion Prevention System (NGIPS) Based Cyber Attacks Classification and Challenges Using Machine Learning Techniques

Abstract

At present, nearly all of international interactions in commerce, economics, culture, social interaction, and government at all level involving individuals, non-governmental organizations, authorities, and governmental institutions take occur online. Cyberattacks and hazards related to technology for wireless communication have become major issues for numerous government agencies and private businesses worldwide in recent times. Today's society relies heavily on electronic technology, and protecting this data against cyberattacks is a challenging issue. The motive behind cyberattacks is to financially harm companies. Next-Generation Intrusion Prevention System (NGIPS) keeps an eye on devices and network traffic for known suspicious tasks, suspect activity by alerting security administrators about known or potential dangers, or by sending alerts to a centralized security tool, an IDS can assist speed up and automate network threat Classification and Detection. In this paper Presenting Cyber Attacks Classification using Various Machine Learning techniques with Datasets and Accuracy.