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
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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
Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection
Authors: Ruimin Sun, Xiaoyong Yuan, Pan He, Qile Zhu, Aokun Chen, Andre Gregio, Daniela Oliveira, Xiaolin Li | Published: 2017-12-04 | Updated: 2021-10-17
The best defense is a good offense: Countering black box attacks by predicting slightly wrong labels
Authors: Yannic Kilcher, Thomas Hofmann | Published: 2017-11-15
Towards Reverse-Engineering Black-Box Neural Networks
Authors: Seong Joon Oh, Max Augustin, Bernt Schiele, Mario Fritz | Published: 2017-11-06 | Updated: 2018-02-14
Neural Trojans
Authors: Yuntao Liu, Yang Xie, Ankur Srivastava | Published: 2017-10-03
Detection of Unauthorized IoT Devices Using Machine Learning Techniques
Authors: Yair Meidan, Michael Bohadana, Asaf Shabtai, Martin Ochoa, Nils Ole Tippenhauer, Juan Davis Guarnizo, Yuval Elovici | Published: 2017-09-14