Date of Award

12-2024

Document Type

Project

Degree Name

Master of Science in Information Systems and Technology

Department

Information and Decision Sciences

First Reader/Committee Chair

Dr. Conrad Shayo

Abstract

The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) technologies within food supply chains has led to significant operational efficiencies but has also introduced cybersecurity vulnerabilities, especially from third-party vendors supplying critical software and hardware. This study explores these vulnerabilities and evaluates multi-layered defense strategies to mitigate the cybersecurity risks they introduce. The research questions guiding this study are: (Q1) How do third-party vendors contribute to cybersecurity vulnerabilities within AI-IoT systems in the food industry? (Q2) How can multi-layered defense strategies effectively mitigate the cybersecurity risks introduced by these vendors?

Using a systematic literature review (SLR) approach based on adapted PRISMA guidelines, this study synthesizes recent research on AI-IoT vulnerabilities and defense mechanisms in food industry applications. Findings highlight that third-party vendors often fail to implement robust security measures, leading to vulnerabilities like data integrity compromises and unauthorized access. Defense strategies, including blockchain-enhanced transparency and AI-driven threat intelligence, demonstrate promise in strengthening the cybersecurity of AI-IoT food systems. The study concludes with recommendations for cross-industry standardization and enhanced vendor compliance to secure food supply chains from emerging cyber threats. Future research should further explore blockchain scalability and advanced AI models for real-time threat detection to enhance resilience in this sector.

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