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Utilizing Generative Adversarial Networks to develop a robust Defensive System against Adversarial Examples

Isaac Tumwine, Justin Nshunguye
2022 IJARCCE  
Using the special ability of Generative Adversarial Networks (GANs) to create fresh adversarial instances for model retraining, we offer a novel defense strategy against adversarial examples in this study. In order to achieve this, we create an automated pipeline that combines a convolutional neural network that has already been trained with an external GAN called the Pix2Pix conditional GAN. This pipeline allows us to identify the transformations between adversarial examples and clean data as
more » ... ell as create new adversarial examples on the fly. In an iterative pipeline, these adversarial samples are used to strengthen the model, attack, and defense. Our simulation findings show that the suggested strategy works well.
doi:10.17148/ijarcce.2022.111001 fatcat:ryguphjhlfah5mqd3vqqcnyxae