most citedLarge Language Model Federated Learning with Blockchain and Unlearning for Cross-Organizational Collaboration

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2025

A Framework to Prevent Biometric Data Leakage in the Immersive Technologies Domain

Keshav Sood, Iynkaran Natgunanathan, Uthayasanker Thayasivam +3

Doubtlessly, the immersive technologies have potential to ease people's life and uplift economy, however the obvious data privacy risks cannot be ignored. For example, a participan…

cs.CR2025

Data Sharing, Privacy and Security Considerations in the Energy Sector: A Review from Technical Landscape to Regulatory Specifications

Shiliang Zhang, Sabita Maharjan, Lee Andrew Bygrave +1

Decarbonization, decentralization and digitalization are the three key elements driving the twin energy transition. The energy system is evolving to a more data driven ecosystem, l…

cs.CR2025

HawkEye: Statically and Accurately Profiling the Communication Cost of Models in Multi-party Learning

Wenqiang Ruan, Xin Lin, Ruisheng Zhou +3

Multi-party computation (MPC) based machine learning, referred to as multi-party learning (MPL), has become an important technology for utilizing data from multiple parties with pr…

cs.CR20241 cited

Large Language Model Federated Learning with Blockchain and Unlearning for Cross-Organizational Collaboration

Xuhan Zuo, Minghao Wang, Tianqing Zhu +2

Large language models (LLMs) have transformed the way computers understand and process human language, but using them effectively across different organizations remains still diffi…

cs.AI2024

New Emerged Security and Privacy of Pre-trained Model: a Survey and Outlook

Meng Yang, Tianqing Zhu, Chi Liu +3

Thanks to the explosive growth of data and the development of computational resources, it is possible to build pre-trained models that can achieve outstanding performance on variou…