Abstract: Endpoint security is a critical aspect of modern cybersecurity, as endpoints are often the primary targets for malware and malicious activities. Endpoint Security solutions play a crucial role in protecting these endpoints by detecting and mitigating malware threats. However, the effectiveness of Endpoint Security solutions can be significantly enhanced by leveraging the valuable insights provided by endpoint security component’s informative logs. Artificial intelligence (AI) and machine learning (ML) techniques have emerged as powerful tools in the fight against cyber threats. This review paper explores the various techniques and strategies on the use of AI and ML specifically in leveraging different types of Endpoint security component logs or events to enhance endpoint security. By analyzing and interpreting these logs, organizations can gain valuable insights into potential security incidents, detect anomalies, and improve threat detection capabilities.
Keywords: Endpoint Security Logs, Antimalware logs, Firewall Logs, Endpoint Security, XDR, EDR, Endpoint Detection and Response (EDR), Extended Detection and Response (XDR), Enhancing cyber security, log collection and correlations, Threat Detection, Responding to endpoint threats.
Title: Enhancing Endpoint Security Using Artificial Intelligence and Machine Learning Leveraging Endpoint Security Component Logs
Author: Mohammed Mujtaba, Aseel A Omair, Rawan A Zowaid
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 13, Issue 3, July 2025 - September 2025
Page No: 182-184
Research Publish Journals
Website: www.researchpublish.com
Published Date: 22-September-2025
