Adversarial Diffusion Attacks on Graph-based Traffic Prediction Models

Real-time traffic prediction models play a pivotal role in smart mobility systems and have been widely used in route guidance, emerging mobility services, and advanced traffic management systems. With the availability of massive traffic data, neural network-based deep learning methods, especially gr...

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Veröffentlicht in:	IEEE internet of things journal 2024-01, Vol.11 (1), p.1-1
Hauptverfasser:	Zhu, Lyuyi, Feng, Kairui, Pu, Ziyuan, Ma, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Adversarial Attack Algorithms Approximation Artificial neural networks Deep learning Edge computing Graph Convolutional Network Greedy algorithms Intelligent Transportation Systems Internet of Things Machine learning Management systems Nodes Performance degradation Prediction algorithms Prediction models Predictive models Regularization Robustness Task analysis Traffic information Traffic models Traffic Prediction
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