Mingyuan Fan

Orcid: 0000-0001-9550-9237

Affiliations:
  • East China Normal University, Shanghai, China


According to our database1, Mingyuan Fan authored at least 21 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Privacy-Enhancing and Robust Backdoor Defense for Federated Learning on Heterogeneous Data.
IEEE Trans. Inf. Forensics Secur., 2024

EIUP: A Training-Free Approach to Erase Non-Compliant Concepts Conditioned on Implicit Unsafe Prompts.
CoRR, 2024

SemiAdv: Query-Efficient Black-Box Adversarial Attack with Unlabeled Images.
CoRR, 2024

Guardian: Guarding against Gradient Leakage with Provable Defense for Federated Learning.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

FedMCP: Parameter-Efficient Federated Learning with Model-Contrastive Personalization.
Proceedings of the 30th IEEE International Conference on Parallel and Distributed Systems, 2024

LST2A: Lexical-Syntactic Targeted Adversarial Attack for Texts.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

SGFL-Attack: A Similarity-Guidance Strategy for Hard-Label Textual Adversarial Attack Based on Feedback Learning.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Flatness-aware Adversarial Attack.
CoRR, 2023

On the Trustworthiness Landscape of State-of-the-art Generative Models: A Comprehensive Survey.
CoRR, 2023

Enhance Transferability of Adversarial Examples with Model Architecture.
Proceedings of the IEEE International Conference on Acoustics, 2023

On the Robustness of Split Learning Against Adversarial Attacks.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
Toward Evaluating the Reliability of Deep-Neural-Network-Based IoT Devices.
IEEE Internet Things J., 2022

Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning.
CoRR, 2022

MaskBlock: Transferable Adversarial Examples with Bayes Approach.
CoRR, 2022

Defense against Backdoor Attacks via Identifying and Purifying Bad Neurons.
CoRR, 2022

Case-Aware Adversarial Training.
CoRR, 2022

Enhance transferability of adversarial examples with model architecture.
CoRR, 2022

Dynamically Selected Mixup Machine Unlearning.
Proceedings of the IEEE International Conference on Trust, 2022

Backdoor Defense with Machine Unlearning.
Proceedings of the IEEE INFOCOM 2022, 2022

Combating False Sense of Security: Breaking the Defense of Adversarial Training Via Non-Gradient Adversarial Attack.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Towards Transferable Adversarial Examples Using Meta Learning.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2021


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