A new privacy-preserving Euclid-distance protocol and its applications in WSNs |
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Authors: | Chen Ping Ji Yimu Wang Ruchuan Huang Haiping Zhang Dan |
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Affiliation: | 1. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China 2. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China 3. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China;Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education,Nanjing University of Posts and Telecommunications.Nanjing 210003.China |
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Abstract: | Recently, privacy concerns become an increasingly critical issue. Secure multi-party computation plays an important role in privacy-preserving. Secure multi-party computational geometry is a new field of secure multi-party 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 Euclid-distance between two private vectors without disclosing the private input to each other. A general privacy-preserving Euclid-distance 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 Euclid-distance protocol and Density-Based 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 side. |
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Keywords: | Secure multi-party computation Privacy-preserving Euclid-distance protocol Wireless Sensor Networks (WSNs) Density-Based Clustering Protocol (DBCP) |
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