Advances in computational intelligence and robotics book series, Год журнала: 2025, Номер unknown, С. 307 - 338

Опубликована: Апрель 8, 2025

The rapid digital transformation of agriculture through smart farming technologies has introduced new cybersecurity challenges that threaten the integrity, confidentiality, and availability critical agricultural data systems. As precision agriculture, Internet Things (IoT)-enabled sensors, automated decision-making become integral to modern farming, risks associated with cyber threats—such as breaches, ransomware attacks, supply chain vulnerabilities—continue escalate. Unlike traditional security measures, AI-driven solutions, including deep learning Large Language Models (LLMs), offer real-time threat detection, adaptive defense mechanisms, enhanced risk assessment capabilities. This chapter explores application these in securing networks, from intrusion detection incident response. It also presents case studies solutions implemented environments.

Язык: Английский