Authors: Ping Chen Yimu Ji Ruchuan Wang Haiping Huang Dan Zhang
Publish Date: 2013/01/24
Volume: 30, Issue: 2, Pages: 190-197
Abstract
Recently privacy concerns become an increasingly critical issue Secure multiparty computation plays an important role in privacypreserving Secure multiparty computational geometry is a new field of secure multiparty computation In this paper we devote to investigating the solutions to some secure geometric problems in a cooperative environment The problem is collaboratively computing the Eucliddistance between two private vectors without disclosing the private input to each other A general privacypreserving Eucliddistance protocol is firstly presented as a building block and is proved to be secure and efficient in the comparison with the previous methods And we proposed a new protocol for the application in Wireless Sensor Networks WSNs based on the novel Eucliddistance protocol and DensityBased Clustering Protocol DBCP so that the nodes from two sides can compute cooperatively to divide them into clusters without disclosing their location information to the opposite sideSupported by the National Natural Science Foundation of China No 61170065 61003039 Postdoctoral Foundation 2012M511753 1101011B Science Technology Innovation Fund for Higher Education Institutions of Jiangsu Province CXLX12 0486 and the Priority Academic Program Development of Jiangsu Higher Education Institutions yx002001
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