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What is Hybrid IDS for IoT Security Enhancement about?

This paper proposes a hybrid convolutional neural network model for intrusion detection in IoT networks. The proposed model monitors network traffic and remote nodes to identify attacks in the shortest time possible. It was experimentally tested and found to achieve 98% detection accuracy, which is 3% higher than a traditional RNN model. Key aspects of the proposed system include data collection, preprocessing, network training to detect attacks, and alerting network administrators of security issues. The h

Author

Sarah Salameh

Language

EN