Enhancing IoT-Based Smart Farming Security with a Hybrid GRU Intrusion Detection System

The growing use of IoT devices in smart agriculture makes the industry vulnerable to several cyber risks. This study introduces an innovative hybrid Intrusion Detection System (IDS) utilising Gated Recurrent Units (GRUs) to improve the security of IoT-enabled smart agriculture. compared to current LSTM and CNN-based intrusion detection systems, the proposed model effectively incorporates sequential data dependencies, hence minimising false positives and enhancing detection accuracy. Experimental findings indicate that the suggested model surpasses conventional techniques, with an accuracy of 97.5%, an F1 score of 0.96, and a recall of 0.97. These developments create a strong, efficient, and scalable solution for safeguarding IoT-based agricultural systems from cyber-attacks.