conftrace_

gradient attack

16 papers

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Co-occurring keywords

federated learning (1333) model poisoning (49) adversarial attack (1621) distributed learning (563) evasion attack (31) privacy leakage (105) gradient inversion (21) split learning (20) byzantine attack (17) model inversion (31)

Papers

IBAS:Imperceptible Backdoor Attacks in Split Learning with Limited Information AAAI 2025
DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification NIPS 2024
Safely Learning with Private Data: A Federated Learning Framework for Large Language Model EMNLP 2024
Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data NIPS 2024
TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases NIPS 2024
Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks ICML 2023
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning IJCAI 2022
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks ICML 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification ICML 2022
Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios IJCAI 2022
Recovering Private Text in Federated Learning of Language Models NIPS 2022
TAG: Gradient Attack on Transformer-based Language Models EMNLP 2021
Revealing and Protecting Labels in Distributed Training NIPS 2021
On Breaking Deep Generative Model-based Defenses and Beyond ICML 2020
TextHide: Tackling Data Privacy in Language Understanding Tasks EMNLP 2020
A Little Is Enough: Circumventing Defenses For Distributed Learning NIPS 2019