Document Type

Article

Publication Date

2026

DOI

10.3390/app16188943

Publication Title

Applied Sciences

Volume

16

Issue

18

Pages

8943 (17 pp.)

Abstract

Modern agriculture’s integration of Internet of Things (IoT), Industrial Control Systems (ICSs), and data analytics boosts productivity but introduces significant cybersecurity and data governance challenges. Existing scholarship is divided between policy-focused governance and technical attack analyses, hindering the development of comprehensive, enforceable defenses. This paper introduces an integrated framework that bridges normative data governance in smart farming (SF) with empirical, honeynet-derived threat intelligence. Drawing on the authors’ previous systematic review of SF data governance and a honeynet simulating agricultural IoT/ICS, the study maps governance challenges to quantitative attack indicators from honeynet logs, classifying each pairing as directly supported by telemetry, indirectly supported by telemetry, or not observable using the current methodology. The findings show that the services flagged as governance concerns face sustained attack pressure: the honeynet recorded brute-force attempts against SSH/Telnet on simulated irrigation controllers (149,000 events), connection and login attempts targeting SMB (Server Message Block) and MQTT (Message Queuing Telemetry Transport) on automated machinery (67,156), credential-guessing attempts against management services (14,937), and ICS protocol probes (11,532). Geographic and protocol distributions reveal that legacy industrial protocols and weakly authenticated management interfaces, both highlighted as governance concerns, constitute the primary attack surface. This evidence supports a tiered governance model integrating protocol-level controls, identity governance, and data-sharing policy, demonstrating that effective SF cybersecurity requires empirically calibrated rather than purely policy-driven frameworks. The proposed framework offers actionable guidance for aligning technical defenses with data governance obligations. This work contributes a new methodological protocol (cross-evidentiary mapping), an empirically calibrated tiered framework, and a coherent research agenda at the intersection of governance and measurement, serving as a template for similar analyses in other critical infrastructure sectors.

Rights

© 2026 by the authors.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.

Data Availability

Article states: "No new data were created for this synthesis. The corpus of the literature review is documented in [5]. The honeynet dataset behind the aggregated metrics in Table 2, comprising sanitized event logs, honeypot and Suricata configurations, and analysis scripts, was collected in the companion study [6] and is available from the corresponding author on reasonable request. The raw logs are not posted publicly because they contain source IP addresses."

Original Publication Citation

Rouzky, R., Sarrafzadeh, A., Sowells-Boone, E., Green, J., Pasandi, H. B., & Goins, G. (2026). Bridging governance and empirical threat intelligence: An integrated framework for cybersecurity in smart farming. Applied Sciences, 16(18), Article 8943. https://doi.org/10.3390/app16188943

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