Cross-Technology Signal Detection and Jamming Attack for Heterogeneous Internet of Things

Researchers developed an AI-based attack system that can identify and jam wireless communications across different IoT protocols (Wi-Fi, ZigBee, BLE) operating in the 2.4 GHz frequency band. The system uses deep learning models (LSTM neural networks with attention mechanisms) trained on channel state information (CSI, the detailed characteristics of wireless signals) to classify signal types with over 96% accuracy, then employs reinforcement learning (a type of AI that learns through trial and error) to intelligently decide when and how to jam these communications. Tests showed the attack successfully disrupted ZigBee and BLE device performance while remaining difficult to detect.