Locally differentially private graph clustering via structure-preserving graph compression

Locally differentially private clustering is an effective approach to uncover latent structures in decentralized social graphs while preserving individual privacy. Existing solutions encode graph data using adjacency bit vectors, whose high dimensionality introduces substantial differential noise an