Practical Privacy-Preserving K-means Clustering
Payman Mohassel, Mike Rosulek, Ni Trieu · DOAJ (DOAJ: Directory of Open Access Journals) · 2020
Clustering is a common technique for data analysis, which aims to partition data into similar groups. When the data comes from different sources, it is highly desirable to maintain the privacy of each database. In this work, we study a popular clustering algorithm (K-means) and adapt it to the privacypreserving context.