University of Victoria

Published purpose

The increasing frequency and sophistication of ransomware attacks poses significant threats to the integrity and resilience of supply chain networks. Despite the significant financial and operational impact of such attacks, existing defensive mechanisms are still embryonic. Most available ransomware solutions are designed for conventional networks and do not consider the unique characteristics of supply chains, such as the domino effect that an infection can create. In response, this project proposes to develop an innovative approach that integrates machine learning techniques with risk management strategies to enhance the detection of ransomware threats within supply chain ecosystems.