Stateful Detection of Model Extraction Attacks
Authors: Soham Pal, Yash Gupta, Aditya Kanade, Shirish Shevade | Published: 2021-07-12
Attack Rules: An Adversarial Approach to Generate Attacks for Industrial Control Systems using Machine Learning
Authors: Muhammad Azmi Umer, Chuadhry Mujeeb Ahmed, Muhammad Taha Jilani, Aditya P. Mathur | Published: 2021-07-11
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