Privacy-preserving cox regression for survival analysis
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy-preserving classification of vertically partitioned data via random kernels
ACM Transactions on Knowledge Discovery from Data (TKDD)
Secure Multi-party Protocols for Privacy Preserving Data Mining
WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
Secure two and multi-party association rule mining
CISDA'09 Proceedings of the Second IEEE international conference on Computational intelligence for security and defense applications
A classification based framework for privacy preserving data mining
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
Bands of privacy preserving objectives: classification of PPDM strategies
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
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For the problem of decision tree classification with privacy concerns, we propose several efficient secure multi-party computation protocols to construct a privacy preserving ID3 algorithm over horizontally partitioned data among multiple parties. Our algorithm presents the first solution to privacy preserving decision tree classification among more than two parties. We also make a performance comparison with the existing solution, which is only applicable to the twoparty case. The result shows that our solution has a significantly better performance.