Feedback Learning for Improving the Robustness of Neural Networks
Authors: Chang Song, Zuoguan Wang, Hai Li | Published: 2019-09-12
敵対的サンプル
Localized Adversarial Training for Increased Accuracy and Robustness in Image Classification
Authors: Eitan Rothberg, Tingting Chen, Luo Jie, Hao Ji | Published: 2019-09-10
Effectiveness of Adversarial Examples and Defenses for Malware Classification
Authors: Robert Podschwadt, Hassan Takabi | Published: 2019-09-10
Learning to Disentangle Robust and Vulnerable Features for Adversarial Detection
Authors: Byunggill Joe, Sung Ju Hwang, Insik Shin | Published: 2019-09-10
BOSH: An Efficient Meta Algorithm for Decision-based Attacks
Authors: Zhenxin Xiao, Puyudi Yang, Yuchen Jiang, Kai-Wei Chang, Cho-Jui Hsieh | Published: 2019-09-10 | Updated: 2019-10-14
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures
Authors: Gil Fidel, Ron Bitton, Asaf Shabtai | Published: 2019-09-08
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses
Authors: Uyeong Jang, Susmit Jha, Somesh Jha | Published: 2019-09-07 | Updated: 2020-02-17
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation
Authors: Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, Pushmeet Kohli | Published: 2019-09-03 | Updated: 2019-12-20
High Accuracy and High Fidelity Extraction of Neural Networks
Authors: Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, Nicolas Papernot | Published: 2019-09-03 | Updated: 2020-03-03
Universal, transferable and targeted adversarial attacks
Authors: Junde Wu, Rao Fu | Published: 2019-08-29 | Updated: 2022-06-13