Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls

arXiv:2405.09318v1 Announce Type: new
Abstract: In the current cybersecurity landscape, protecting military devices such as communication and battlefield management systems against sophisticated cyber attacks is crucial. Malware exploits vulnerabilities through stealth methods, often evading traditional detection mechanisms such as software signatures. The application of ML/DL in vulnerability detection has been extensively explored in the literature. However, current ML/DL vulnerability detection methods struggle with understanding the context and intent behind complex attacks. Integrating large language models (LLMs) with system call analysis …

application arxiv attacks battlefield communication cs.cr cs.lg current cyber cyber attacks cybersecurity cybersecurity landscape detection devices exploits language language models large malware malware detection management management systems military protecting signatures software stealth system systems transfer vulnerabilities