Year: 2024
Type: article
Abstract: In an era where digital transformation is ubiquitous, cybersecurity has emerged as a critical concern for individuals, organizations, and governments alike.Traditional security measures, while effective to a certain extent, often fall short in addressing the sophisticated and evolving nature of cyber threats.Artificial Intelligence (AI) has surfaced as a promising solution to enhance cybersecurity by automating threat detection, response, and mitigation processes.This paper explores the integration of AI technologies in cybersecurity, focusing on machine learning algorithms, neural networks, and natural language processing (NLP) techniques.We analyze various AIdriven cybersecurity applications, including intrusion detection systems, malware analysis, and threat intelligence platforms.The methodology involves a comprehensive review of existing literature, followed by empirical analysis using publicly available cybersecurity datasets.Results indicate that AI significantly improves the accuracy and efficiency of threat detection and response mechanisms.However, challenges such as data privacy, algorithmic bias, and the need for continuous learning remain prevalent.The study concludes by highlighting the potential of AI to revolutionize cybersecurity practices while emphasizing the importance of addressing its inherent limitations.
Author: Sandeep Reddy Gudimetla
Institution: HCL Technologies (United States)
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405674348