Why Blocking Targeted Adversarial Perturbations Impairs the Ability to Learn
Authors: Ziv Katzir, Yuval Elovici | Published: 2019-07-11
Deep Learning Method
Neutaint: Efficient Dynamic Taint Analysis with Neural Networks
Authors: Dongdong She, Yizheng Chen, Abhishek Shah, Baishakhi Ray, Suman Jana | Published: 2019-07-08 | Updated: 2019-09-03
QUOTIENT: Two-Party Secure Neural Network Training and Prediction
Authors: Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner, Adrià Gascón | Published: 2019-07-08
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
Authors: Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison Cottrell, Geoffrey Hinton | Published: 2019-07-05 | Updated: 2020-02-18
Adversarial Robustness through Local Linearization
Authors: Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli | Published: 2019-07-04 | Updated: 2019-10-10
MimosaNet: An Unrobust Neural Network Preventing Model Stealing
Authors: Kálmán Szentannai, Jalal Al-Afandi, András Horváth | Published: 2019-07-02
Accurate, reliable and fast robustness evaluation
Authors: Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge | Published: 2019-07-01 | Updated: 2019-12-12
Comment on “Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network”
Authors: Roland S. Zimmermann | Published: 2019-07-01
Adversarial Robustness via Label-Smoothing
Authors: Morgane Goibert, Elvis Dohmatob | Published: 2019-06-27 | Updated: 2019-10-15
Adversarial Examples to Fool Iris Recognition Systems
Authors: Sobhan Soleymani, Ali Dabouei, Jeremy Dawson, Nasser M. Nasrabadi | Published: 2019-06-21 | Updated: 2019-07-18