4 papers
Communication-Efficient Publication of Sparse Vectors under Differential Privacy
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
In this work, we propose a differentially private algorithm for publishing matrices aggregated from sparse vectors. These matrices include social network adjacency matrices, user-i…
Facility Location Problem under Local Differential Privacy without Super-set Assumption
Kevin Pfisterer, Quentin Hillebrand, Vorapong Suppakitpaisarn
In this paper, we introduce an adaptation of the facility location problem and analyze it within the framework of local differential privacy (LDP). Under this model, we ensure the…
Counting Graphlets of Size under Local Differential Privacy
Vorapong Suppakitpaisarn, Donlapark Ponnoprat, Nicha Hirankarn +1
The problem of counting subgraphs or graphlets under local differential privacy is an important challenge that has attracted significant attention from researchers. However, much o…
Local Differential Privacy for Number of Paths and Katz Centrality
Louis Betzer, Vorapong Suppakitpaisarn, Quentin Hillebrand
In this paper, we give an algorithm to publish the number of paths and Katz centrality under the local differential privacy (LDP), providing a thorough theoretical analysis. Althou…