@techreport{oai:ipsj.ixsq.nii.ac.jp:00233376,
 author = {Quentin, Hillebrand and Vorapong, Suppakitpaisarn and Tetsuo, Shibuya and Quentin, Hillebrand and Vorapong, Suppakitpaisarn and Tetsuo, Shibuya},
 issue = {1},
 month = {Mar},
 note = {This article introduces a new triangle counting algorithm under the framework of edge local differential privacy leveraging the degeneracy-bounded nature of real-world graphs. We describe a pre-processing step that performs a re-ordering of the vertices according to their degrees. Despite its small budget usage, this ordering effectively reduces the occurrence of some specific patterns in the graph. In turn, the diminished number of those patterns enable our triangle counting algorithm to minimize its error on the estimation. This results in the error of our triangle counting scaling as a function of the degeneracy unlike state of the art algorithms for which it was scaling with the maximal degree, effectively increasing the accuracy in practice., This article introduces a new triangle counting algorithm under the framework of edge local differential privacy leveraging the degeneracy-bounded nature of real-world graphs. We describe a pre-processing step that performs a re-ordering of the vertices according to their degrees. Despite its small budget usage, this ordering effectively reduces the occurrence of some specific patterns in the graph. In turn, the diminished number of those patterns enable our triangle counting algorithm to minimize its error on the estimation. This results in the error of our triangle counting scaling as a function of the degeneracy unlike state of the art algorithms for which it was scaling with the maximal degree, effectively increasing the accuracy in practice.},
 title = {Private Triangle Counting for Degeneracy-bounded Graphs},
 year = {2024}
}