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Found 2 papers, 1 papers with code
A Generative Model based Adversarial Security of Deep Learning and Linear Classifier Models
In this paper, we have proposed a mitigation method for adversarial attacks against machine learning models with an autoencoder model that is one of the generative ones.
Data Augmentation Based Malware Detection using Convolutional Neural Networks
The main contributions of the paper's model structure consist of three components, including image generation from malware samples, image augmentation, and the last one is classifying the malware families by using a convolutional neural network model.
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