Nicolas Papernot
3 papers in the PaperMetrix corpus
Papers by this author
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Adversarial Attacks on Neural Network Policies
2017 · arXiv (Cornell University)
Machine learning classifiers are known to be vulnerable to inputs maliciously constructed by adversaries to force misclassification. Such adversarial examples have been extensively studied in the context of computer vision applications. In this work, we …
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Architectural Backdoors in Neural Networks
2022 · arXiv (Cornell University)
Machine learning is vulnerable to adversarial manipulation. Previous literature has demonstrated that at the training stage attackers can manipulate data and data sampling procedures to control model behaviour. A common attack goal is to plant …
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On the Limitations of Stochastic Pre-processing Defenses
2022 · arXiv (Cornell University)
Defending against adversarial examples remains an open problem. A common belief is that randomness at inference increases the cost of finding adversarial inputs. An example of such a defense is to apply a random transformation …