MASTER Assignment
Utilizing Generative Artificial Intelligence to enhance Cyber Resilience in Cyber Supply Chain Management
Type : Master M-CS
Period: March, 2024 - August, 2024
Student : Márton, A.Z. (Antónia Zsófia, Student M-CS)
Date Final project: August 29, 2024
Supervisors:
Abstract:
This thesis addresses critical challenges in supply chain management by focusing on the enhancement of cyber resilience and visibility through the integration of N-tier mapping and generative AI. The study identifies the limitations of traditional strategies, which are increasingly inadequate in managing the growing complexity and vulnerability of global supply chains, particularly in the context of evolving cyber threats. The research investigates the transformative potential of Large Language Models (LLMs) when applied within multi-agent systems to automate and optimize supply chain monitoring processes. Although current N-tier mapping frameworks are effective, they can still rely on manual procedures. This thesis demonstrates that the integration of advanced AI technologies can significantly improve the efficiency of these processes. The findings indicate that automating the N-tier mapping process and leveraging generative AI can substantially enhance supply chain resilience and visibility, leading to more secure and efficient operations. However, the study also underscores the challenges associated with deploying AI in real-world scenarios, highlighting the need for further research and development in this area.