Adversarial for Good? How the Adversarial ML Community’s Values Impede Socially Beneficial Uses of Attacks
Authors: Kendra Albert, Maggie Delano, Bogdan Kulynych, Ram Shankar Siva Kumar | Published: 2021-07-11 | Updated: 2021-09-15
Hack The Box: Fooling Deep Learning Abstraction-Based Monitors
Authors: Sara Hajj Ibrahim, Mohamed Nassar | Published: 2021-07-10 | Updated: 2021-07-18
Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform
Authors: Bo Liu, Chaowei Tan, Jiazhou Wang, Tao Zeng, Huasong Shan, Houpu Yao, Heng Huang, Peng Dai, Liefeng Bo, Yanqing Chen | Published: 2021-07-08 | Updated: 2021-07-30
Malware Classification Using Deep Boosted Learning
Authors: Muhammad Asam, Saddam Hussain Khan, Tauseef Jamal, Umme Zahoora, Asifullah Khan | Published: 2021-07-08
Analytically Tractable Hidden-States Inference in Bayesian Neural Networks
Authors: Luong-Ha Nguyen, James-A. Goulet | Published: 2021-07-08
Understanding Intrinsic Robustness Using Label Uncertainty
Authors: Xiao Zhang, David Evans | Published: 2021-07-07 | Updated: 2022-03-17
Principles for Evaluation of AI/ML Model Performance and Robustness
Authors: Olivia Brown, Andrew Curtis, Justin Goodwin | Published: 2021-07-06
A Low-Cost Machine Learning Based Network Intrusion Detection System with Data Privacy Preservation
Authors: Jyoti Fakirah, Lauhim Mahfuz Zishan, Roshni Mooruth, Michael N. Johnstone, Wencheng Yang | Published: 2021-07-06
Understanding the Security of Deepfake Detection
Authors: Xiaoyu Cao, Neil Zhenqiang Gong | Published: 2021-07-05 | Updated: 2021-10-06
Machine Learning for Fraud Detection in E-Commerce: A Research Agenda
Authors: Niek Tax, Kees Jan de Vries, Mathijs de Jong, Nikoleta Dosoula, Bram van den Akker, Jon Smith, Olivier Thuong, Lucas Bernardi | Published: 2021-07-05