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Mixture GAN For Modulation Classification Resiliency Against Adversarial Attacks
In this paper, we propose a novel generative adversarial network (GAN)-based countermeasure approach to safeguard the DNN-based AMC systems against adversarial attack examples.
A New Dimensionality Reduction Method Based on Hensel's Compression for Privacy Protection in Federated Learning
The proposed approach overcomes the problem of privacy leakage due to composition by applying DP only once before the training; clients train their local model on the privacy-preserving dataset generated by the second layer.
Secrecy Rate Maximization for Hardware Impaired Untrusted Relaying Network with Deep Learning
To satisfy low-latency as one of the main key performance indicators (KPI) required in beyond 5G (B5G) communications, a computationally efficient data-driven approach is developed exploiting a deep learning model to improve the ASR while the computational burden is significantly reduced.
