STRIDE-based Cyber Security Threat Modeling for IoT-enabled Precision Agriculture Systems

TL;DR

This paper applies STRIDE-based threat modeling to IoT-enabled precision agriculture systems, identifying 58 potential security threats and providing mitigation suggestions to enhance cybersecurity in smart farming.

Contribution

It presents a comprehensive threat model for precision agriculture infrastructure using STRIDE, highlighting vulnerabilities and proposing security mitigation strategies.

Findings

Identified 58 potential security threats in precision agriculture systems.

Provided systematic mitigation suggestions for identified threats.

Enhanced understanding of cybersecurity challenges in IoT-enabled agriculture.

Abstract

The concept of traditional farming is changing rapidly with the introduction of smart technologies like the Internet of Things (IoT). Under the concept of smart agriculture, precision agriculture is gaining popularity to enable Decision Support System (DSS)-based farming management that utilizes widespread IoT sensors and wireless connectivity to enable automated detection and optimization of resources. Undoubtedly the success of the system would be impacted on crop productivity, where failure would impact severely. Like many other cyber-physical systems, one of the growing challenges to avoid system adversity is to ensure the system's security, privacy, and trust. But what are the vulnerabilities, threats, and security issues we should consider while deploying precision agriculture? This paper has conducted a holistic threat modeling on component levels of precision agriculture's standard infrastructure using popular threat intelligence tools STRIDE to identify common security issues. Our modeling identifies a noticing of fifty-eight potential security threats to consider. This presentation systematically presented them and advised general mitigation suggestions to support cyber security in precision agriculture.