A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks
Authors: Jinghui Chen, Dongruo Zhou, Jinfeng Yi, Quanquan Gu | Published: 2018-11-27 | Updated: 2019-09-15
バックドアモデルの検知
The Taboo Trap: Behavioural Detection of Adversarial Samples
Authors: Ilia Shumailov, Yiren Zhao, Robert Mullins, Ross Anderson | Published: 2018-11-18 | Updated: 2019-11-21
Shallow-Deep Networks: Understanding and Mitigating Network Overthinking
Authors: Yigitcan Kaya, Sanghyun Hong, Tudor Dumitras | Published: 2018-10-16 | Updated: 2019-05-09
Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection
Authors: Omar M. K. Alhawi, James Baldwin, Ali Dehghantanha | Published: 2018-07-27
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks
Authors: Kang Liu, Brendan Dolan-Gavitt, Siddharth Garg | Published: 2018-05-30
Detecting Deceptive Reviews using Generative Adversarial Networks
Authors: Hojjat Aghakhani, Aravind Machiry, Shirin Nilizadeh, Christopher Kruegel, Giovanni Vigna | Published: 2018-05-25
A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content
Authors: Joshua Saxe, Richard Harang, Cody Wild, Hillary Sanders | Published: 2018-04-13
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks
Authors: Pu Zhao, Sijia Liu, Yanzhi Wang, Xue Lin | Published: 2018-04-09
Combating Adversarial Attacks Using Sparse Representations
Authors: Soorya Gopalakrishnan, Zhinus Marzi, Upamanyu Madhow, Ramtin Pedarsani | Published: 2018-03-11 | Updated: 2018-07-13
DANCin SEQ2SEQ: Fooling Text Classifiers with Adversarial Text Example Generation
Authors: Catherine Wong | Published: 2017-12-14