New Incremental Privacy-Preserving Clustering Protocols

Saeed Samet, Ali Miri
2013 Lecture Notes on Software Engineering  
We consider the problem of data clustering on streamed data, when the number of transactions is growing very quickly, or when data is distributed among several parties and their privacy is a concern. In this paper we present two new protocols for incremental privacy-preserving k-means clustering, which is a very popular data mining method, when data is distributed, horizontally or vertically, among multiple parties. At the end of each protocol, each party, without revealing its own private
more » ... ts own private data, receives the final result of the clustering algorithm. Also, to improve efficiency, previous knowledge is used to incrementally update the centers and membership of each cluster. Index Terms-Clustering, security and privacy-preserving, incremental algorithms, data mining and machine learning, distributed data structures.
doi:10.7763/lnse.2013.v1.53 fatcat:ydbdgnbw45espgcmfa2qgkqyve