Law and Adversarial Machine Learning
Authors: Ram Shankar Siva Kumar, David R. O'Brien, Kendra Albert, Salome Vilojen | Published: 2018-10-25 | Updated: 2018-12-05
Adversarial Example Detection
One Bit Matters: Understanding Adversarial Examples as the Abuse of Redundancy
Authors: Jingkang Wang, Ruoxi Jia, Gerald Friedland, Bo Li, Costas Spanos | Published: 2018-10-23
A Training-based Identification Approach to VIN Adversarial Examples
Authors: Yingdi Wang, Wenjia Niu, Tong Chen, Yingxiao Xiang, Jingjing Liu, Gang Li, Jiqiang Liu | Published: 2018-10-18
DeepImageSpam: Deep Learning based Image Spam Detection
Authors: Amara Dinesh Kumar, Vinayakumar R, Soman KP | Published: 2018-10-03
Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples
Authors: Dan Peng, Zizhan Zheng, Xiaofeng Zhang | Published: 2018-09-08 | Updated: 2018-12-22
Are adversarial examples inevitable?
Authors: Ali Shafahi, W. Ronny Huang, Christoph Studer, Soheil Feizi, Tom Goldstein | Published: 2018-09-06 | Updated: 2020-02-03
HASP: A High-Performance Adaptive Mobile Security Enhancement Against Malicious Speech Recognition
Authors: Zirui Xu, Fuxun Yu, Chenchen Liu, Xiang Chen | Published: 2018-09-04
MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks
Authors: Siwakorn Srisakaokul, Yuhao Zhang, Zexuan Zhong, Wei Yang, Tao Xie, Bo Li | Published: 2018-08-31 | Updated: 2019-07-27
Security and Privacy Issues in Deep Learning
Authors: Ho Bae, Jaehee Jang, Dahuin Jung, Hyemi Jang, Heonseok Ha, Hyungyu Lee, Sungroh Yoon | Published: 2018-07-31 | Updated: 2021-03-10
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Authors: Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin | Published: 2018-07-10 | Updated: 2018-10-27