Leveraging Large Language Models for Cybersecurity Risk Assessment: A Case from Forestry Cyber-Physical Systems

Abstract

This paper explores the potential of locally hosted LLMs with retrieval-augmented generation to support cybersecurity risk assessment in the forestry domain. Based on interviews and sessions with 12 experts, the study finds that LLMs can assist in generating initial risk assessments and identifying threats, while human oversight remains essential for accuracy and compliance.

Mazen Mohamad

Researcher at RISE Research Institutes of Sweden

My research interests include Safety & Cybersecurity of Autonomous Systems, AI4Security, and Security4AI.