Research On Secure Multiparty Ranking

As one of the hot research field in information security, secure multiparty computation is research on two or more parties want to compute a task with each other in the distributed networks, it must ensure the privacy of participants. Today, with the rapid development of the internet, more and more trading-online and informa-tion interaction are occurred on the internet. Many sensitive information exposed on t-he internet which leaking the privacy of users. So, it is very important to study some relative questions about SMC.Currently research on secure multiparty computation mainly focused on two aspects:one is the research on the basic theory of SMC, including research on the definition of model, design basic protocols of SMC and find general solutions to the SMC. There are a lot of achievements such as the definition of malicious model and semi-honest model, the specific security requirements definition and some general solution to the SMC. The other one is research on some specific application environment relative to secure multiparty computation make the SMC solution has more application value.Although it has been got many achievements in theoretical research and practical application, a lot questions are worth to be researched in SMC field. In1998. O.GoldReich pointed out the protocol efficiency will be very lower and cannot reach ideal effect when we use general solution to solve specific SMC problem. We can design efficient SMC protocol to solve specific problem. It is the further study of these scientists that makes secure multiparty ranking differentiated more new directions worthy of research, such as electronic elections, private information retrieval, fair trade the protection of private information used for scientific computing, computational geometry, which secure multiparty ranking is an important issue, and it also has a very important role in the field of national security, military, and commercial.Secure Multiparty Ranking can be described as:a number of participants P1,P2,...,Pn based on their private information si(i=1.2,...,n) execute a confidential function f(s1,s2,...,sn).on the condition of not disclosing each other’s private information getting their own rank position in the ranked sequence s1,s2,...,sn.According to the differiation of the participate of each agreement, the secure multiparty ranking can be divided into agreement with a trusted third party agreement and without a trusted third party agreements; According to the differiation of the number of the agreement participants, it can be divided into two-party secret data comparison (which is comparison secretly) and multi-party secret data ranking; According to private data that the party involved has. it can be divided into secure multiparty single data ranking and security multi-party multi-data ranking. In addition, we can also divide it into malicious secure multiparty ranking model and semi-honest model according to the honesty of the participants. Secure multiparty ranking secure multiparty computation is of great value in both theory and practical application。The article mainly study’s the problem of secure multi-party ranking and its extensions under the semi-honest model, the main work are as follows:First, we introduce the latest research for secure multiparty ranking, by describing the solutions to several classic Yao’s millionaires’ problem and secure multiparty ranking, and summarizing it.Second, we study secure two-party vector dominance statistic problem. The protocol security and efficiency is very lower in existing secure two-party vector dominance statistic protocol rely on oblivious third party. To address this situation, this paper proposes a new secure two-party vector dominance statistic protocol without oblivious third party based on homomorphic encryption and vector cross protocol, and make a theoretical analysis of the safety and efficiency of the protocol, at last,by comparing with the existing protocol, the new protocol has more advantages on communication cost and security, and on the basis of the new protocol, put forward a secure components sum of two vectors protocol and a secure components multiplication of two vectors protocol, and correspondingly making a theoretical analysis of two-expanded protocol.Third, we study secure multiparty ranking problem. By Analyzing and summarizing the existing protocol, putting forward an extension of the security multiparty multiplication protocol, which make the parties involved get the multiplication of all private data, and theoretically analyze the correctness, security and efficiency of the new multiparty multiplication protocol, and then put forward a new secure multiparty ranking protocol by using a special ranking encoding, so that the participating parties can obtain the rank of their owns privacy data s1in a sequence s1,s2,....sn sorted ascending, theoretically analyzing the correctness, security and efficiency of the new secret sort protocol, reflecting the advantages of the new protocol security and communication cost by comparing with the existing protocol.