Using Large Language Models to Mitigate Ransomware Threats
Fang Wang
Abstract
This paper explores the application of Large Language Models (LLMs), such as GPT-3 and GPT-4, in generating cybersecurity policies and strategies to mitigate ransomware threats, including data theft ransomware. We discuss the strengths and limitations of LLMs for ransomware defense and provide recommendations for effectively leveraging LLMs while ensuring ethical compliance. The key contributions include a quantitative evaluation of LLM-generated policies, an examination of the legal and ethical implications, and an analysis of how LLMs can enhance ransomware resilience when applied judiciously.
Topics & Concepts
RansomwareComputer securityResilience (materials science)Key (lock)BusinessInternet privacyRisk analysis (engineering)Computer scienceMalwareThermodynamicsPhysicsAdvanced Malware Detection TechniquesDigital and Cyber ForensicsInformation and Cyber Security