Copertina

Verification of Machine Unlearning is Fragile

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Binchi, Chen, Zihan, Shen, Cong, Li, Jundong
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Cryptography and Security
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Certified Defense on the Fairness of Graph Neural Networks
di: Dong, Yushun, et al.
Pubblicazione: (2023)

TruVRF: Towards Triple-Granularity Verification on Machine Unlearning
di: Zhou, Chunyi, et al.
Pubblicazione: (2024)

Contrastive Unlearning: A Contrastive Approach to Machine Unlearning
di: Lee, Hong kyu, et al.
Pubblicazione: (2024)

Adversarial Machine Unlearning
di: Di, Zonglin, et al.
Pubblicazione: (2024)

LMEraser: Large Model Unlearning through Adaptive Prompt Tuning
di: Xu, Jie, et al.
Pubblicazione: (2024)

Certified Machine Unlearning via Noisy Stochastic Gradient Descent
di: Chien, Eli, et al.
Pubblicazione: (2024)

Towards Irreversible Machine Unlearning for Diffusion Models
di: Yuan, Xun, et al.
Pubblicazione: (2025)

Federated Unlearning for Human Activity Recognition
di: Chen, Kongyang, et al.
Pubblicazione: (2024)

Towards Unveiling Vulnerabilities of Large Reasoning Models in Machine Unlearning
di: Chen, Aobo, et al.
Pubblicazione: (2026)

MUBox: A Critical Evaluation Framework of Deep Machine Unlearning
di: Li, Xiang, et al.
Pubblicazione: (2025)

Privacy Preservation through Practical Machine Unlearning
di: Dilworth, Robert
Pubblicazione: (2025)

Forgetting Similar Samples: Can Machine Unlearning Do it Better?
di: Xu, Heng, et al.
Pubblicazione: (2026)

Towards Efficient Target-Level Machine Unlearning Based on Essential Graph
di: Xu, Heng, et al.
Pubblicazione: (2024)

BadFU: Backdoor Federated Learning through Adversarial Machine Unlearning
di: Lu, Bingguang, et al.
Pubblicazione: (2025)

Reinforcement Unlearning
di: Ye, Dayong, et al.
Pubblicazione: (2023)

Classification-Head Bias in Class-Level Machine Unlearning: Diagnosis, Mitigation, and Evaluation
di: Zheng, Weidong, et al.
Pubblicazione: (2026)

Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
di: Bertran, Martin, et al.
Pubblicazione: (2024)

SoK: Machine Unlearning for Large Language Models
di: Ren, Jie, et al.
Pubblicazione: (2025)

TAPE: Tailored Posterior Difference for Auditing of Machine Unlearning
di: Wang, Weiqi, et al.
Pubblicazione: (2025)

Distributional Machine Unlearning via Selective Data Removal
di: Allouah, Youssef, et al.
Pubblicazione: (2025)

SCU: An Efficient Machine Unlearning Scheme for Deep Learning Enabled Semantic Communications
di: Wang, Weiqi, et al.
Pubblicazione: (2025)

Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios
di: Huang, Tao, et al.
Pubblicazione: (2024)

Graph Neural Network Explanations are Fragile
di: Li, Jiate, et al.
Pubblicazione: (2024)

Machine Unlearning: Taxonomy, Metrics, Applications, Challenges, and Prospects
di: Li, Na, et al.
Pubblicazione: (2024)

Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
di: Zhang, Jiahao, et al.
Pubblicazione: (2026)

Survey of Security and Data Attacks on Machine Unlearning In Financial and E-Commerce
di: Brodzinski, Carl E. J.
Pubblicazione: (2024)

A Robust Certified Machine Unlearning Method Under Distribution Shift
di: Guo, Jinduo, et al.
Pubblicazione: (2026)

Visual CoT Makes VLMs Smarter but More Fragile
di: Xu, Chunxue, et al.
Pubblicazione: (2025)

Machine Unlearning for Traditional Models and Large Language Models: A Short Survey
di: Xu, Yi
Pubblicazione: (2024)

Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Approximate Unlearning Completeness
di: Wang, Cheng-Long, et al.
Pubblicazione: (2024)

Node-level Contrastive Unlearning on Graph Neural Networks
di: Lee, Hong kyu, et al.
Pubblicazione: (2025)

Rectifying Privacy and Efficacy Measurements in Machine Unlearning: A New Inference Attack Perspective
di: Naderloui, Nima, et al.
Pubblicazione: (2025)

Unlink to Unlearn: Simplifying Edge Unlearning in GNNs
di: Tan, Jiajun, et al.
Pubblicazione: (2024)

Goldfish: An Efficient Federated Unlearning Framework
di: Wang, Houzhe, et al.
Pubblicazione: (2024)

Graph Unlearning with Efficient Partial Retraining
di: Zhang, Jiahao, et al.
Pubblicazione: (2024)

Verifiable Unlearning on Edge
di: Maheri, Mohammad M, et al.
Pubblicazione: (2025)

Edge Unlearning is Not "on Edge"! An Adaptive Exact Unlearning System on Resource-Constrained Devices
di: Xia, Xiaoyu, et al.
Pubblicazione: (2024)

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data
di: Inane, Ahmed Mehdi, et al.
Pubblicazione: (2026)

Conditional Adversarial Fragility in Financial Machine Learning under Macroeconomic Stress
di: Baviskar, Samruddhi
Pubblicazione: (2025)

On The Fragility of Benchmark Contamination Detection in Reasoning Models
di: Wang, Han, et al.
Pubblicazione: (2025)