This project presents a genetic algorithm (GA) based approach for attacking neural networks, as well as several options for defending against such attacks. The model used in this study is MobileNetV2, a widely used lightweight image classification model, which is trained on the CIFAR-10 dataset.
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Frederico-lp/Adversarial-Attacking-and-Defending-of-NN
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