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Found 3 papers, 1 papers with code
Expediting Neural Network Verification via Network Reduction
Furthermore, the experiment results also show that network reduction can improve the availability of existing verification tools on many networks by reducing them into sequential neural networks.
ExploreADV: Towards exploratory attack for Neural Networks
Although deep learning has made remarkable progress in processing various types of data such as images, text and speech, they are known to be susceptible to adversarial perturbations: perturbations specifically designed and added to the input to make the target model produce erroneous output.
VulDeePecker: A Deep Learning-Based System for Vulnerability Detection
Since deep learning is motivated to deal with problems that are very different from the problem of vulnerability detection, we need some guiding principles for applying deep learning to vulnerability detection.
