ArticleScientific reports2025
A novel cyber threat intelligence platform for evaluating the risk associated with smart agriculture.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Cybersecurity and resiliency in agricultural and food systems.Nature food · 2026Review
- A quantum-driven multi-stage framework integrating variational entanglement, reinforcement learning, and federated explainability for climate-resilient farming.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid proliferation of Internet of Things (IoT) devices has brought about a profound transformation in our daily lives and work environments. However, this proliferation has also given rise to significant security challenges, as cybercriminals increasingly target IoT devices to exploit vulnerabilities and gain access to sensitive data. This escalating threat landscape poses a severe issue across diverse domains where IoT is deployed, including agriculture, healthcare, and surveillance. In the realm of agriculture, where farmers have historically contended with pests and environmental challenges, a new adversary has emerged in the form of cyber criminals. The agriculture sector has witnessed a surge in cyber-attacks targeting smart agriculture solutions despite being a relatively recent addition to the industry. Farmers may not have control over the actions of cyber adversaries, but they possess the ability to make informed purchasing decisions when adopting smart farming solutions and implementing fundamental security measures, such as robust user credentials and regular system updates. In this regard, this research introduces a groundbreaking approach to addressing the cybersecurity concerns associated with smart agriculture-deception technology. Overall, deception technology involves the creation of deceptive elements, including decoys, traps, and false information, designed to divert cybercriminals away from genuine data and systems where this research presents a novel cyber threat intelligence platform that leverages deception technology to assess and mitigate the risks associated with smart agriculture as the first of its kind research. Based on the insights derived from the experimental work, actionable recommendations would be provided to relevant stakeholders on how to mitigate cyber risks and bolster the security posture of IoT-enabled smart agriculture. Overall, this innovative approach represents a significant step towards safeguarding the increasingly interconnected world of smart agriculture, offering a promising avenue for defending against the escalating cyber threats faced by this vital industry.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.