Image de couverture de livre

Federated TrustChain: Blockchain-Enhanced LLM Training and Unlearning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zuo, Xuhan, Wang, Minghao, Zhu, Tianqing, Zhang, Lefeng, Ye, Dayong, Yu, Shui, Zhou, Wanlei
Format:	Preprint
Publié:	2024
Sujets:	Cryptography and Security
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Federated Learning with Blockchain-Enhanced Machine Unlearning: A Trustworthy Approach
par: Zuo, Xuhan, et autres
Publié: (2024)

Large Language Model Federated Learning with Blockchain and Unlearning for Cross-Organizational Collaboration
par: Zuo, Xuhan, et autres
Publié: (2024)

Really Unlearned? Verifying Machine Unlearning via Influential Sample Pairs
par: Xu, Heng, et autres
Publié: (2024)

Forgetting Similar Samples: Can Machine Unlearning Do it Better?
par: Xu, Heng, et autres
Publié: (2026)

When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
par: Wang, Shang, et autres
Publié: (2024)

Update Selective Parameters: Federated Machine Unlearning Based on Model Explanation
par: Xu, Heng, et autres
Publié: (2024)

Towards Transparent and Incentive-Compatible Collaboration in Decentralized LLM Multi-Agent Systems: A Blockchain-Driven Approach
par: Qi, Minfeng, et autres
Publié: (2025)

Towards Efficient Target-Level Machine Unlearning Based on Essential Graph
par: Xu, Heng, et autres
Publié: (2024)

Defending Against Neural Network Model Inversion Attacks via Data Poisoning
par: Zhou, Shuai, et autres
Publié: (2024)

QUEEN: Query Unlearning against Model Extraction
par: Chen, Huajie, et autres
Publié: (2024)

TrustChain: A Blockchain Framework for Auditing and Verifying Aggregators in Decentralized Federated Learning
par: Hallaji, Ehsan, et autres
Publié: (2025)

The Emerged Security and Privacy of LLM Agent: A Survey with Case Studies
par: He, Feng, et autres
Publié: (2024)

Evaluating of Machine Unlearning: Robustness Verification Without Prior Modifications
par: Xu, Heng, et autres
Publié: (2024)

Reinforcement Unlearning
par: Ye, Dayong, et autres
Publié: (2023)

Data Duplication: A Novel Multi-Purpose Attack Paradigm in Machine Unlearning
par: Ye, Dayong, et autres
Publié: (2025)

Don't Forget Too Much: Towards Machine Unlearning on Feature Level
par: Xu, Heng, et autres
Publié: (2024)

Unique Security and Privacy Threats of Large Language Models: A Comprehensive Survey
par: Wang, Shang, et autres
Publié: (2024)

Secure Forgetting: A Framework for Privacy-Driven Unlearning in Large Language Model (LLM)-Based Agents
par: Ye, Dayong, et autres
Publié: (2026)

Data-Free Model-Related Attacks: Unleashing the Potential of Generative AI
par: Ye, Dayong, et autres
Publié: (2025)

Unreal Thinking: Chain-of-Thought Hijacking via Two-stage Backdoor
par: Chang, Wenhan, et autres
Publié: (2026)

Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives
par: Wang, Linlin, et autres
Publié: (2024)

Turning Black Box into White Box: Dataset Distillation Leaks
par: Chen, Huajie, et autres
Publié: (2026)

Zero-shot Class Unlearning via Layer-wise Relevance Analysis and Neuronal Path Perturbation
par: Chang, Wenhan, et autres
Publié: (2024)

Chain-of-Lure: A Universal Jailbreak Attack Framework using Unconstrained Synthetic Narratives
par: Chang, Wenhan, et autres
Publié: (2025)

Large Language Models Merging for Enhancing the Link Stealing Attack on Graph Neural Networks
par: Guan, Faqian, et autres
Publié: (2024)

Privacy Intelligence: A Survey on Image Privacy in Online Social Networks
par: Liu, Chi, et autres
Publié: (2020)

When LLMs Team Up: A Coordinated Attack Framework for Automated Cyber Intrusions
par: Qi, Minfeng, et autres
Publié: (2026)

A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
par: Liu, Hengzhu, et autres
Publié: (2024)

Poisoning the Pixels: Revisiting Backdoor Attacks on Semantic Segmentation
par: Zhang, Guangsheng, et autres
Publié: (2026)

Frequency Bias Matters: Diving into Robust and Generalized Deep Image Forgery Detection
par: Liu, Chi, et autres
Publié: (2025)

Towards Robust GAN-generated Image Detection: a Multi-view Completion Representation
par: Liu, Chi, et autres
Publié: (2023)

Blockchain-enabled Trustworthy Federated Unlearning
par: Lin, Yijing, et autres
Publié: (2024)

The Trust Paradox in LLM-Based Multi-Agent Systems: When Collaboration Becomes a Security Vulnerability
par: Xu, Zijie, et autres
Publié: (2025)

MARS: A Malignity-Aware Backdoor Defense in Federated Learning
par: Wan, Wei, et autres
Publié: (2025)

On the Hidden Costs of Counterfactual Knowledge Training in LLM Unlearning
par: Ye, Xiaotian, et autres
Publié: (2026)

Specular: Towards Secure, Trust-minimized Optimistic Blockchain Execution
par: Ye, Zhe, et autres
Publié: (2022)

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs
par: Wang, Linlin, et autres
Publié: (2025)

CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning
par: Wang, Weiqi, et autres
Publié: (2025)

Machine Unlearning: A Comprehensive Survey
par: Wang, Weiqi, et autres
Publié: (2024)

CSC: Turning the Adversary's Poison against Itself
par: Shi, Yuchen, et autres
Publié: (2026)