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A Protocol of Secure Multi-party Multi-data Ranking and Its Application in Privacy Preserving Sequential Pattern Mining

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4 Author(s)
Liu Wen ; Sch. of Comput., Commun. Univ. of China, Beijing, China ; Luo Shou-shan ; Wang Yong-bin ; Jiang Zhen-tao

A secure multi-party multi-data ranking protocol was proposed, which was not related to any specific encryption algorithm. And it was shown that the protocol was correct and secure in the semi-honest model. A privacy-preserving sequential pattern mining solution was also designed based on secure multi-party sum protocol and secure multi-party multi-data raking protocol and a simple analysis of this solution was given. This solution can be used in many aspects: privacy-preserving consumptive action analysis of multi-marketplace, privacy-preserving disease diagnose of multi-hospital and so on.

Published in:

Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on

Date of Conference:

15-19 April 2011