@inproceedings{cc6d12a842cd4fc6b7c1f9ede81a5735,
title = "Private Spectral Clustering Over Binary Stochastic Block Models",
abstract = "We investigate privacy-preserving spectral clustering for community detection within stochastic block models (SBMs). Specifically, we focus on edge differential privacy (DP) and propose private algorithms for community recovery. Our work explores the fundamental trade-offs between the privacy budget and the accurate recovery of community labels. Furthermore, we establish information-theoretic conditions that guarantee the accuracy of our methods, providing theoretical assurances for successful community recovery under edge DP.",
keywords = "Community Detection, Differential Privacy, Graphs, Perturbation, Spectral Clustering, Stochastic Block Model",
author = "Mohamed Seif and Antti Koskela and Goldsmith, \{Andrea J.\}",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE International Symposium on Information Theory, ISIT 2025 ; Conference date: 22-06-2025 Through 27-06-2025",
year = "2025",
doi = "10.1109/ISIT63088.2025.11195399",
language = "English (US)",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ISIT 2025 - 2025 IEEE International Symposium on Information Theory, Proceedings",
address = "United States",
}