Digital Forensics in Agriculture: A Systematic Analysis of Security Challenges, Tools, and Applications in Smart Farming

Abstract

The emergence of Agriculture 4.0 has led to a significant transformation in farming practices through the integration of smart technologies, including Internet of Things (IoT) devices, drones, autonomous machinery, and cloud-based platforms. While these advancements have enhanced operational efficiency and data-driven decision-making, they have also introduced complex cybersecurity risks and digital vulnerabilities. In response to these threats, digital forensics has become an essential discipline for identifying, collecting, analyzing, and preserving digital evidence within agricultural systems. This paper presents a comprehensive and systematic analysis of the current state of digital forensics in agriculture, drawing upon literature published between 2018 and 2024. It explores the unique forensic challenges posed by heterogeneous Ag-IoT environments, limited tool compatibility, real-time data volatility, and legal considerations. Emerging technologies such as artificial intelligence, machine learning, blockchain, and drone forensics are examined for their potential to enhance forensic capabilities in smart farming contexts. Real-world case studies are analyzed to illustrate practical challenges and gaps in forensic readiness. The review concludes by identifying critical areas for future research, emphasizing the need for scalable forensic frameworks, specialized training, and robust policy development to support secure and resilient agricultural ecosystems.