By analyzing current cybersecurity trends and the application of artificial intelligence in protective mechanisms, the study provides valuable insights into future research pathways aimed at establishing secure and sustainable agricultural technologies.
Abstract
The integration of technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) is fueling a shift toward smart farming, unlocking a fundamental change in how agriculture is practiced through new precision agriculture techniques. While these innovations enhance efficiency and streamline routine agricultural operations, they also introduce a range of new threats and vulnerabilities within smart farming ecosystems. This research differentiates itself within the field of smart farming security. It achieves this through an integrated examination of systemic vulnerabilities across the entire agricultural technology stack. Organized into four core sections, i.e., sensing, network, cloud, and application layers, it systematically identifies the specific security risks associated with each layer, including data leakage, signal injection, cyberattacks, and manipulation of artificial intelligence systems. The paper further discusses appropriate countermeasures designed to mitigate these risks and underscores the importance of adopting integrated defense strategies. By analyzing current cybersecurity trends and the application of artificial intelligence in protective mechanisms, the study provides valuable insights into future research pathways aimed at establishing secure and sustainable agricultural technologies.
A comprehensive framework for analyzing CS challenges in PA is introduced by systematically identification and classification key CS parameters and its sub-parameters, threats, risks, and their potential impacts across advanced technique and drone-enabled agricultural settings.
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By combining digital sensing, network connectivity, data-driven analyses, cloud services, and automated controls, smart farming has been increasingly adopted in agricultural production. Although these technologies have improved the precision and efficiency of farm management, they also increase cybersecurity exposure a...
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An integrated framework that bridges normative data governance in smart farming with empirical, honeynet-derived threat intelligence is introduced, demonstrating that effective SF cybersecurity requires empirically calibrated rather than purely policy-driven frameworks.
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The emergence of cyber-physical systems in agricultural production has created unprecedented opportunities for precision farming while simultaneously introducing substantial security vulnerabilities. This research addresses the critical challenge of distinguishing sensor anomalies from malicious cyber-attacks in resour...
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It is argued that securing the IoT ecosystem requires sustained, coordinated effort from manufacturers, regulators and end-users, and where current technological and regulatory responses fall short of that goal is identified.
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