Adversarial Attacks on Machine Learning Cybersecurity Defences in Industrial Control Systems
Authors: Eirini Anthi, Lowri Williams, Matilda Rhode, Pete Burnap, Adam Wedgbury | Published: 2020-04-10
Defense Method
TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems
Authors: Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu | Published: 2020-04-09
Adversarial Genetic Programming for Cyber Security: A Rising Application Domain Where GP Matters
Authors: Una-May O'Reilly, Jamal Toutouh, Marcos Pertierra, Daniel Prado Sanchez, Dennis Garcia, Anthony Erb Luogo, Jonathan Kelly, Erik Hemberg | Published: 2020-04-07
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
Authors: David Enthoven, Zaid Al-Ars | Published: 2020-04-01
Adversarial Perturbations Fool Deepfake Detectors
Authors: Apurva Gandhi, Shomik Jain | Published: 2020-03-24 | Updated: 2020-05-15
Systematic Evaluation of Privacy Risks of Machine Learning Models
Authors: Liwei Song, Prateek Mittal | Published: 2020-03-24 | Updated: 2020-12-09
Certified Defenses for Adversarial Patches
Authors: Ping-Yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein | Published: 2020-03-14 | Updated: 2020-09-25
A Survey of Adversarial Learning on Graphs
Authors: Liang Chen, Jintang Li, Jiaying Peng, Tao Xie, Zengxu Cao, Kun Xu, Xiangnan He, Zibin Zheng, Bingzhe Wu | Published: 2020-03-10 | Updated: 2022-04-05
Dynamic Backdoor Attacks Against Machine Learning Models
Authors: Ahmed Salem, Rui Wen, Michael Backes, Shiqing Ma, Yang Zhang | Published: 2020-03-07 | Updated: 2022-03-03
Confusing and Detecting ML Adversarial Attacks with Injected Attractors
Authors: Jiyi Zhang, Ee-Chien Chang, Hwee Kuan Lee | Published: 2020-03-05 | Updated: 2021-03-08