Privacy-Preserving Naive Bayesian Classification over Horizontally Partitioned Data

Protection of privacy is a critical problem in data mining. Preserving data privacy in distributed data mining is even more challenging. In this paper, we consider the problem of privacy-preserving naive Bayesian classiflcation over vertically partitioned data. The problem is one of important issues in privacy- preserving distributed data mining. Our approach is based on homomorphic encryption. The scheme is very e-cient in the term of computation and communication cost.

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