Enhanced Security against Adversarial Examples Using a Random Ensemble
of Encrypted Vision Transformer Models

Enhanced Security against Adversarial Examples Using a Random Ensemble of Encrypted Vision Transformer Models

26 July 2023

Hitoshi Kiya

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Papers citing "Enhanced Security against Adversarial Examples Using a Random Ensemble of Encrypted Vision Transformer Models"

14 / 14 papers shown

Title
Privacy-Preserving Image Classification Using Isotropic Network Maungmaung Aprilpyone Hitoshi Kiya 37 36 0 16 Apr 2022
A Protection Method of Trained CNN Model Using Feature Maps Transformed With Secret Key From Unauthorized Access Maungmaung Aprilpyone Hitoshi Kiya 39 5 0 01 Sep 2021
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense Maungmaung Aprilpyone Hitoshi Kiya 60 57 0 02 Oct 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 56 32 0 16 May 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 227 1,858 0 03 Mar 2020
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 88 992 0 29 Nov 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 101 490 0 03 Jul 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 130 754 0 31 May 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 86 439 0 25 Jan 2019
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 315 12,131 0 19 Jun 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 472 3,148 0 04 Nov 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 268 8,579 0 16 Aug 2016
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 154 4,905 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014