AI for Threat Detection and Mitigation: Using AI to Identify and Respond to Cybersecurity Threats in Real-Time

AI for Threat Detection and Mitigation: Using AI to Identify and Respond to Cybersecurity Threats in Real-Time

Gaurav Kashyap, Independent researcher,

gauravkec2005@gmail.com

Abstract

As the digital landscape evolves and cyber threats become increasingly sophisticated, traditional security systems struggle to keep up with the volume, variety, and velocity of attacks. Artificial Intelligence (AI) has emerged as a powerful tool for enhancing cybersecurity by enabling the automated detection, analysis, and mitigation of threats in real-time. By leveraging machine learning (ML) algorithms, natural language processing (NLP), and anomaly detection, AI can process vast amounts of data, identify patterns, and respond to potential threats faster and more accurately than conventional methods. This paper explores the role of AI in modern cybersecurity, focusing on its applications in threat detection and mitigation. It examines how AI systems, such as intrusion detection systems (IDS), security information and event management (SIEM) platforms, and endpoint protection tools, are being used to combat cyber threats. The paper also discusses the challenges associated with implementing AI in cybersecurity, including false positives, adversarial attacks, and the need for continuous training, and offers insights into future trends in AI-driven threat mitigation.

Keywords: Cyber Security, Artificial Intelligence (AI), Natural Language Processing (NLP), Machine Learning (ML), Deep Learning.

DOI: 10.55041/IJSREM10936