Adversarial Learning

Private Graph Extraction via Feature Explanations

Authors: Iyiola E. Olatunji, Mandeep Rathee, Thorben Funke, Megha Khosla | Published: 2022-06-29 | Updated: 2023-11-02
Attack Methods against DFL
Privacy Risk Management
Adversarial Learning

A Framework for Understanding Model Extraction Attack and Defense

Authors: Xun Xian, Mingyi Hong, Jie Ding | Published: 2022-06-23
Algorithm Design
Membership Inference
Adversarial Learning

ROSE: A RObust and SEcure DNN Watermarking

Authors: Kassem Kallas, Teddy Furon | Published: 2022-06-22
DNN IP Protection Method
Adversarial Learning
Evaluation Method

The Privacy Onion Effect: Memorization is Relative

Authors: Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramer | Published: 2022-06-21 | Updated: 2022-06-22
Membership Inference
Label Inference Attack
Adversarial Learning

Architectural Backdoors in Neural Networks

Authors: Mikel Bober-Irizar, Ilia Shumailov, Yiren Zhao, Robert Mullins, Nicolas Papernot | Published: 2022-06-15
Adversarial Learning
Adversarial attack
Threat Model

Reconstructing Training Data from Trained Neural Networks

Authors: Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani | Published: 2022-06-15 | Updated: 2022-12-05
Hyperparameter Tuning
Performance Evaluation Metrics
Adversarial Learning

Learn to Adapt: Robust Drift Detection in Security Domain

Authors: Aditya Kuppa, Nhien-An Le-Khac | Published: 2022-06-15
Drift Detection Method
Performance Evaluation Metrics
Adversarial Learning

NICGSlowDown: Evaluating the Efficiency Robustness of Neural Image Caption Generation Models

Authors: Simin Chen, Zihe Song, Mirazul Haque, Cong Liu, Wei Yang | Published: 2022-03-29
Model DoS
Adversarial Example
Adversarial Learning

Detect & Reject for Transferability of Black-box Adversarial Attacks Against Network Intrusion Detection Systems

Authors: Islam Debicha, Thibault Debatty, Jean-Michel Dricot, Wim Mees, Tayeb Kenaza | Published: 2021-12-22
Poisoning
Adversarial Learning
Defense Method

Robustness of Graph Neural Networks at Scale

Authors: Simon Geisler, Tobias Schmidt, Hakan Şirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann | Published: 2021-10-26 | Updated: 2023-04-30
Graph Representation Learning
Robustness
Adversarial Learning