Threat Modeling and Attack Surface Analysis of IoT-Enabled Controlled Environment Agriculture Systems
Andrii Vakhnovskyi

TL;DR
This paper develops the first comprehensive threat model for IoT-enabled Controlled Environment Agriculture systems, identifying numerous vulnerabilities and proposing security countermeasures.
Contribution
It introduces a novel threat model for CEA, applies multiple analysis techniques, and highlights unique AI-driven attack classes and security gaps in the industry.
Findings
123 unique threats identified across 25 data-flow elements
10 communication protocols operate without authentication or encryption
Only one CVE issued among surveyed vendors, with no IEC 62443 certifications
Abstract
The United States designates Food and Agriculture as one of sixteen critical infrastructure sectors, yet no mandatory cybersecurity requirements exist for agricultural operations and no formal threat model has been published for Controlled Environment Agriculture (CEA) systems. This paper presents the first comprehensive threat model for IoT-enabled CEA, applying STRIDE analysis, MITRE ATT&CK for ICS mapping, and IEC 62443 zone-and-conduit decomposition to a production platform deployed across 30+ commercial facilities in 8 U.S. climate zones. We enumerate 123 unique threats across 25 data-flow-diagram elements spanning 15 communication protocols, 10 of which operate with zero authentication or encryption by design. We identify five novel attack classes unique to AI-driven CEA: stealth destabilization of neural-network-tuned PID controllers, baseline drift poisoning of anomaly…
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