Hybrid Convolutional Neural Network for Robust Attack Detection in Wireless Sensor Networks

This study presents a hybrid CNN model for detecting attacks in wireless sensor networks. The system analyzes sensor data patterns to identify abnormal or malicious activity. Its deep-learning approach improves accuracy and robustness in threat detection. Designed to strengthen security in distributed IoT and sensor-based environments.

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