Mahmood Sharif

most cited

n

-ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers

5 citations · 5 across the 1 of their papers we have counts for

collaborators

2 papers

cs.CV2019★ 5 cited

$n$ -ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers

Mahmood Sharif, Lujo Bauer, Michael K. Reiter

This paper proposes a new defense called $n$ -ML against adversarial examples, i.e., inputs crafted by perturbing benign inputs by small amounts to induce misclassifications by clas…

cs.CR2018

On the Suitability of $L_{p}$ -norms for Creating and Preventing Adversarial Examples

Mahmood Sharif, Lujo Bauer, Michael K. Reiter

Much research effort has been devoted to better understanding adversarial examples, which are specially crafted inputs to machine-learning models that are perceptually similar to b…

n-ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers

On the Suitability of Lp​-norms for Creating and Preventing Adversarial Examples

$n$ -ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers

On the Suitability of $L_{p}$ -norms for Creating and Preventing Adversarial Examples