Abstract: Network-based Intrusion Detection System is a threat caused by the explosion of computer networks and the myriad of recent content-based threats, which occur daily. As well as an overview of machine learning approaches for signature and anomaly detection methods, this article discusses several machine learning strategies applied to intrusion detection and preprocessing. The NIDS taxonomy and attribute classifier have created classifications and outlines. Machine learning methods are widely utilized in anomaly detection using many data sets. Additional preprocessing methods have been added, for example, sorting and discretization have been applied to the data collection of measured values. Custom methods focused on search algorithms using machine learning that uses novel search algorithms are vulnerable to being revealed. This analysis is highly relevant to the use of machine learning methods used in computer security, which furthers their cause.
Keywords: Intrusion Detection, K-means Algorithm, Machine learning, Swarm Intelligence.
Title: Cyber Attack detection Using Big data analysis
Author: Yazeed Al Moaiad, Yasser Mohamed Abdelrahman Tarshany, Nasir Ahmed Algeelani, Wafa Al-Haithami
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 10, Issue 3, July 2022 - September 2022
Page No: 26-33
Research Publish Journals
Website: www.researchpublish.com
Published Date: 28-July-2022
