Adversarial Examples for Cost-Sensitive Classifiers
Authors: Gavin S. Hartnett, Andrew J. Lohn, Alexander P. Sedlack | Published: 2019-10-04
PINFER: Privacy-Preserving Inference for Machine Learning
Authors: Marc Joye, Fabien A. P. Petitcolas | Published: 2019-10-04
False Data Injection Attacks in Internet of Things and Deep Learning enabled Predictive Analytics
Authors: Gautam Raj Mode, Prasad Calyam, Khaza Anuarul Hoque | Published: 2019-10-03 | Updated: 2019-12-13
BUZz: BUffer Zones for defending adversarial examples in image classification
Authors: Kaleel Mahmood, Phuong Ha Nguyen, Lam M. Nguyen, Thanh Nguyen, Marten van Dijk | Published: 2019-10-03 | Updated: 2020-06-16
A Data Science Approach for Honeypot Detection in Ethereum
Authors: Ramiro Camino, Christof Ferreira Torres, Mathis Baden, Radu State | Published: 2019-10-03 | Updated: 2019-12-19
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions
Authors: He Zhao, Trung Le, Paul Montague, Olivier De Vel, Tamas Abraham, Dinh Phung | Published: 2019-10-03
Piracy Resistant Watermarks for Deep Neural Networks
Authors: Huiying Li, Emily Wenger, Shawn Shan, Ben Y. Zhao, Haitao Zheng | Published: 2019-10-02 | Updated: 2020-12-02
Attacking Vision-based Perception in End-to-End Autonomous Driving Models
Authors: Adith Boloor, Karthik Garimella, Xin He, Christopher Gill, Yevgeniy Vorobeychik, Xuan Zhang | Published: 2019-10-02
Machine-Learning Techniques for Detecting Attacks in SDN
Authors: Mahmoud Said Elsayed, Nhien-An Le-Khac, Soumyabrata Dev, Anca Delia Jurcut | Published: 2019-10-02
Analyzing and Improving Neural Networks by Generating Semantic Counterexamples through Differentiable Rendering
Authors: Lakshya Jain, Varun Chandrasekaran, Uyeong Jang, Wilson Wu, Andrew Lee, Andy Yan, Steven Chen, Somesh Jha, Sanjit A. Seshia | Published: 2019-10-02 | Updated: 2020-07-17