Distributed privacy preserving clustering via homomorphic secret sharing and its application to (Vertically) partitioned spatio-temporal data

International Journal of Data Warehousing and Mining

Volumn 7, Issue 1, 2011, Pages 46-66

  Yildizli, Can ^a   Pedersen, Thomas Brochmann ^a   Saygin, Yucel ^a   Savas, Erkay ^a   Levi, Albert ^a  

^a SABANCI UNIVERSITY   (Turkey)

Author keywords

Clustering; Data mining; Multiparty computation; Privacy preserving data mining; Secret sharing

Indexed keywords

CLUSTERING; COMMUNICATION COST; COMPUTATIONAL COSTS; HOMOMORPHIC SECRET SHARING; K-MEANS CLUSTERING ALGORITHM; MULTIPARTY COMPUTATION; PRIVACY ISSUE; PRIVACY PRESERVING; PRIVACY PRESERVING DATA MINING; REAL-WORLD SCENARIO; REALISTIC SCENARIO; SECRET SHARING; SECURE MULTI-PARTY COMPUTATION; SPATIO-TEMPORAL DATA;

CLUSTERING ALGORITHMS; COMPUTATIONAL EFFICIENCY; CRYPTOGRAPHY; DATA MINING;

DATA PRIVACY;

EID: 79954583952     PISSN: 15483924     EISSN: 15483932     Source Type: Journal    
DOI: 10.4018/jdwm.2011010103     Document Type: Article

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