Model-Guardian: Protecting against Data-Free Model Stealing Using Gradient Representations and Deceptive Predictions
Authors: Yunfei Yang, Xiaojun Chen, Yuexin Xuan, Zhendong Zhao | Published: 2025-03-23
防御効果分析
Rethinking the Defense Against Free-rider Attack From the Perspective of Model Weight Evolving Frequency
Authors: Jinyin Chen, Mingjun Li, Tao Liu, Haibin Zheng, Yao Cheng, Changting Lin | Published: 2022-06-11
Membership Inference Attack on Graph Neural Networks
Authors: Iyiola E. Olatunji, Wolfgang Nejdl, Megha Khosla | Published: 2021-01-17 | Updated: 2021-12-18
FLAME: Taming Backdoors in Federated Learning (Extended Version 1)
Authors: Thien Duc Nguyen, Phillip Rieger, Huili Chen, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Shaza Zeitouni, Farinaz Koushanfar, Ahmad-Reza Sadeghi, Thomas Schneider | Published: 2021-01-06 | Updated: 2023-08-05
On the Effectiveness of Regularization Against Membership Inference Attacks
Authors: Yigitcan Kaya, Sanghyun Hong, Tudor Dumitras | Published: 2020-06-09
Tricking Adversarial Attacks To Fail
Authors: Blerta Lindqvist | Published: 2020-06-08
Exploring the role of Input and Output Layers of a Deep Neural Network in Adversarial Defense
Authors: Jay N. Paranjape, Rahul Kumar Dubey, Vijendran V Gopalan | Published: 2020-06-02
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods
Authors: Kyungmi Lee, Anantha P. Chandrakasan | Published: 2020-06-01
Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries
Authors: Moritz Seiler, Heike Trautmann, Pascal Kerschke | Published: 2020-05-27
Encryption Inspired Adversarial Defense for Visual Classification
Authors: MaungMaung AprilPyone, Hitoshi Kiya | Published: 2020-05-16