Paper Contents
Abstract
In cybersecurity, artificial intelligence is revolutionizing incident response, risk management, and threat identification in a progressively hostile cyber threat landscape. This research presents a thorough literature review on AI in cybersecurity, focusing on both aspects of the balance sheet. This paper discusses how AI-driven technologies like machine learning, deep learning, natural language processing, and expert systems improve security frameworks through predictive analytics, real-time threat intelligence, and anomaly detection. The research explores various uses of AI such as network protection, cloud safety, healthcare, and finance, highlighting how AI-driven solutions enhance the resilience of cybersecurity against attacks. Nonetheless, there are drawbacks too, primarily associated with algorithmic prejudices and aggressive attacks. This paper discusses AI cybersecurity tools like Cylance, Darktrace, and IBM Watson, analyzing their influences and effects on security operations. The study also explores recent advancements and enhancements in AI-driven cybersecurity, ethical concerns, and regulatory structures. To establish a safe digital space, this document highlights the importance of a unified strategy that integrates AI with human expertise, ethics, and regulatory adherence.
Copyright
Copyright © 2025 Arooj Naimuddin Khan . This is an open access article distributed under the Creative Commons Attribution License.
