7 citations · 7 across the 3 of their papers we have counts for
5 papers
HRNet: Differentially Private Hierarchical and Multi-Resolution Network for Human Mobility Data Synthesization
Shun Takagi, Li Xiong, Fumiyuki Kato +2
Human mobility data offers valuable insights for many applications such as urban planning and pandemic response, but its use also raises privacy concerns. In this paper, we introdu…
ULDP-FL: Federated Learning with Across Silo User-Level Differential Privacy
Fumiyuki Kato, Li Xiong, Shun Takagi +2
Differentially Private Federated Learning (DP-FL) has garnered attention as a collaborative machine learning approach that ensures formal privacy. Most DP-FL approaches ensure DP a…
HDPView: Differentially Private Materialized View for Exploring High Dimensional Relational Data
Fumiyuki Kato, Tsubasa Takahashi, Shun Takagi +3
How can we explore the unknown properties of high-dimensional sensitive relational data while preserving privacy? We study how to construct an explorable privacy-preserving materia…
Preventing Manipulation Attack in Local Differential Privacy using Verifiable Randomization Mechanism
Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa
Several randomization mechanisms for local differential privacy (LDP) (e.g., randomized response) are well-studied to improve the utility. However, recent studies show that LDP is…
Secure and Efficient Trajectory-Based Contact Tracing using Trusted Hardware
Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa
The COVID-19 pandemic has prompted technological measures to control the spread of the disease. Private contact tracing (PCT) is one of the promising techniques for the purpose. Ho…