14 citations · 18 across the 7 of their papers we have counts for
4 papers · 1 filter
SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation
Yashothara Shanmugarasa, Ming Ding, M. A. P Chamikara +1
Large language models (LLMs) are sophisticated artificial intelligence systems that enable machines to generate human-like text with remarkable precision. While LLMs offer signific…
From 5G to 6G: A Survey on Security, Privacy, and Standardization Pathways
Mengmeng Yang, Youyang Qu, Thilina Ranbaduge +12
The vision for 6G aims to enhance network capabilities with faster data rates, near-zero latency, and higher capacity, supporting more connected devices and seamless experiences wi…
Realistic Differentially-Private Transmission Power Flow Data Release
David Smith, Frederik Geth, Elliott Vercoe +5
For the modeling, design and planning of future energy transmission networks, it is vital for stakeholders to access faithful and useful power flow data, while provably maintaining…
Differentially Private Release of High-Dimensional Datasets using the Gaussian Copula
Hassan Jameel Asghar, Ming Ding, Thierry Rakotoarivelo +2
We propose a generic mechanism to efficiently release differentially private synthetic versions of high-dimensional datasets with high utility. The core technique in our mechanism…