Semi-trusted Collaborative Framework for Multi-party Computation

• Kok Seng Wong,
• Myung Ho Kim,

Vol. 4, No. 3, June 29, 2010
10.3837/tiis.2010.06.013, Download Paper (Free):

• data sharing
• Privacy Preserving
• secure computation protocol
• collaborative computation

Abstract

Data sharing is an essential process for collaborative works particularly in the banking, finance and healthcare industries. These industries require many collaborative works with their internal and external parties such as branches, clients, and service providers. When data are shared among collaborators, security and privacy concerns becoming crucial issues and cannot be avoided. Privacy is an important issue that is frequently discussed during the development of collaborative systems. It is closely related with the security issues because each of them can affect the other. The tradeoff between privacy and security is an interesting topic that we are going to address in this paper. In view of the practical problems in the existing approaches, we propose a collaborative framework which can be used to facilitate concurrent operations, single point failure problem, and overcome constraints for two-party computation. Two secure computation protocols will be discussed to demonstrate our collaborative framework.

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