Locally Private Subgraph Counting via Noisy Adjacency Matrix and Differential Privacy on Randomized Data

arXiv:2507.06508 · cs.CR · Submitted 2025-07-09 · Read on arXiv

cs.CR

Submitted: 2025-07-09

Updated: 2026-08-26

Terminology

Adjacency Matrix — 48× in this paper · explained in 1 episode
Accuracy — 46× in this paper · explained in 1 episode
Differential Privacy — 41× in this paper · explained in 4 episodes
Noisy Adjacency Matrix — 27× in this paper
Local Differential Privacy — 11× in this paper
Clustering — 3× in this paper · explained in 2 episodes
Core — 3× in this paper · explained in 2 episodes
Differentially Private — 3× in this paper · explained in 3 episodes
Trace — 3× in this paper · explained in 2 episodes
Approximate Counting — 2× in this paper · explained in 1 episode
Randomized Response — 2× in this paper
Annual Symposium on Foundations of Computer Science — 1× in this paper
Degeneracy — 1× in this paper · explained in 3 episodes
Differential Privacy (DP) — 1× in this paper · explained in 7 episodes
Federated Learning — 1× in this paper · explained in 15 episodes
Generate Noisy Adjacency Matrix — 1× in this paper
Mean Squared Error — 1× in this paper
Robustness — 1× in this paper · explained in 5 episodes

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