ISSN (Print): 3078-4018 ISSN (Online): 3078-4018
Hong Kong International Journal of Research Studies Official Publication of Octopus Publication, Hong Kong
Cover of July-December 2024
research article

Using Large Language Models to Discover and Manage Cybersecurity Threats and Software Vulnerabilities

  • Geetha Priya D T
    India
  • Dr. Rajesh Koolwal
    India

Vol. 2 , Issue 2 (2024) · pp. 87-94

Country: India

DOI: 10.64180/octopus.222414

Abstract

The rapid growth of digital systems has significantly increased the complexity and frequency of cybersecurity threats and software vulnerabilities. Traditional security mechanisms often struggle to detect sophisticated, evolving attacks in a timely manner. Recent advances in Large Language Models (LLMs) offer new opportunities to enhance cybersecurity by enabling intelligent analysis of large volumes of unstructured data, including logs, vulnerability reports, threat intelligence feeds, and source code. This study explores the application of LLMs in discovering, analyzing, and managing cybersecurity threats and software vulnerabilities.

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