awesome-ml-attack

ML models' reconstruction attacks and adversarial examples

Content

• About
• Reconstruction attacks
• Adversarial examples
• Implementations

About

This is a list of resources related to the research and development about ml models' reconstruction attacks and adversarial examples

Reconstruction attacks

• Stealing Hyperparameters in Machine Learning, Wang et al. (2018)
• Machine Learning Models that Remember Too Much, Song et al. (2017)
• Towards Measuring Membership Privacy, Long et al. (2017)
• Membership Inference Attacks Against Machine Learning Models, Shokri et al. (2017)
• Towards the Science of Security and Privacy in Machine Learning, Papernot et al. (2016)
• Stealing Machine Learning Models via Prediction APIs, Tramèr et al. (2016)

Adversarial examples

• The Space of Transferable Adversarial Examples, Tramèr et al. (2017)
• Ensemble Adversarial Training: Attacks and Defenses, Tramèr et al. (2017)
• Adversarial Perturbations Against Deep Neural Networks for Malware Classification, Grosse et al. (2017)
• The limitations of deep learning in adversarial settings, Papernot et al. (2016)
• Crafting adversarial input sequences for recurrent neural networks, Papernot et al. (2016)
• Practical Black-Box Attacks against Machine Learning, Papernot et al. (2016)

Implementations

• Machine Learning Models that Remember Too Much, Song et al. (2017)
• Membership Inference Attacks Against Machine Learning Models, Shokri et al. (2017)
• Stealing Machine Learning Models via Prediction APIs, Tramèr et al. (2016)