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An Advanced Cybersecurity Model for High-Tech Farming Using Machine Learning Approach
Abstract
The need for agricultural and food goods has dramatically expanded due to the rapid population growth. Agriculture's reliance on older technologies has rendered them outmoded and unable to meet demand. Agricultural goods' quantity and quality can be improved by integrating data-driven and sensor technology into the agriculture and food production sectors. Nevertheless, it might increase cyber dangers and make the farming environment worse. As a result of cyberattacks, consumers may consume unsafely, and the economy may suffer. Attackers may operate remotely and deed on-field sensors and entirely self-directed vehicles. The motivation of this chapter is to study various cyber-attacks in the smart farming ecosystem and propose a real-time cybersecurity model for a multi-cloud-based hi-tech farming system.
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