364 citations · 721 across the 7 of their papers we have counts for
4 papers · 1 filter
Towards Plausible Graph Anonymization
Yang Zhang, Mathias Humbert, Bartlomiej Surma +3
Social graphs derived from online social interactions contain a wealth of information that is nowadays extensively used by both industry and academia. However, as social graphs con…
On the (Statistical) Detection of Adversarial Examples
Kathrin Grosse, Praveen Manoharan, Nicolas Papernot +2
Machine Learning (ML) models are applied in a variety of tasks such as network intrusion detection or Malware classification. Yet, these models are vulnerable to a class of malicio…
Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Kathrin Grosse, Nicolas Papernot, Praveen Manoharan +2
Deep neural networks, like many other machine learning models, have recently been shown to lack robustness against adversarially crafted inputs. These inputs are derived from regul…
From Closed-world Enforcement to Open-world Assessment of Privacy
Michael Backes, Pascal Berrang, Praveen Manoharan
In this paper, we develop a user-centric privacy framework for quantitatively assessing the exposure of personal information in open settings. Our formalization addresses key-chall…