CNN-LSTM-based IDS on Precision Farming for IIoT data

The world’s balance is entirely based on agriculture; with precision farming, IoT smart agri-sensor, and intelligent methods, food production is continuous and balanced. If these innovative tools face intrusion attacks, this balanced may be destroyed; to prevent these issues, we need an Intrusion Detection System (IDS) to provide security and privacy to these wireless sensor networks. In the proposed work, we have created an IDS framework using the CNN and LSTM method named CNNLSTM IDS, which can easily sense attacks of different types. The HIKARI-2021 dataset is used to train the architecture to gain accuracy of 93.27 for training and validation.