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

Author

Liu Wen ; Luo Shou-shan ; Wang Yong-bin ; Jiang Zhen-tao

Author_Institution

Sch. of Comput., Commun. Univ. of China, Beijing, China

fYear

2011

fDate

15-19 April 2011

Firstpage

272

Lastpage

275

Abstract

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.

Keywords

cryptographic protocols; data mining; data privacy; encryption algorithm; multihospital; multimarketplace; privacy preserving sequential pattern mining; privacy-preserving consumptive action analysis; privacy-preserving disease diagnosis; secure multiparty multidata ranking protocol; secure multiparty sum protocol; Additives; Data privacy; Databases; Encryption; Protocols; multi-party multi-data ranking; privacy preserving sequential pattern mining; secure multi-party computation; threshold additive homomorphic encryption;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Yunnan

Print_ISBN

978-1-4244-9712-6

Electronic_ISBN

978-0-7695-4335-2

Type

conf

DOI

10.1109/CSO.2011.53

Filename

5957659