The integration of sixth-generation (6G) networks with Wireless Sensor Networks (WSNs) creates unprecedented opportunities for developing secure and scalable smart city infrastructures. However, the proliferation of heterogeneous devices and exponential data growth demand more robust security solutions. While existing hybrid deep learning approaches combining convolutional, recurrent, and attention-based architectures show promise in attack detection, they face limitations including high false-positive rates, inadequate modeling of topological dependencies, and vulnerability to adversarial attacks. This paper presents an enhanced intrusion detection framework that integrates Graph Neural Net... More >