Haralampos-G. Stratigopoulos

Sponge attacks can inflate the energy consumption of Spiking Neural Networks by up to 2.6 times without compromising classification accuracy, posing a serious threat to battery-operated edge devices.

Achieving over 99% accuracy in RF signal recognition tasks while maintaining a latency of just 98 µs per frame could revolutionize spectrum intelligence applications on edge devices.

Wireless chips are vulnerable: a compacted CNN can detect covert channels with high accuracy and efficiency, enabling real-time security directly at the RF receiver.