A privacy-preserving online reverse multi-attributes auction scheme based on degree-matching

Abstract

In recent years, online auction system obtains the widespread application with the vigorous development of e-commerce. During the process of an auction, numbers of qualified suppliers propose their own bidding according to procurements demands. Then the winner is generated by comparing and sorting all of degree-matching between procurers ideal solution and suppliers’ bidding, we remind it as Ideal Degree-Matching Determined Solution (IDDS). IDDS requires suppliers to provide their private information to the auction servers. However, suppliers usually do not expect the real information of the bid leaked out, especially known by other competitors. In this paper we propose a Privacy-Preserving Online Reverse Multi-Attributes Auction Scheme based on Degree-Matching (PRMA). IDDS is used as the basis of determining the auction winner. Impressively based on the difficulty of integer factorization assumption, our scheme ensures data security of all suppliers. Compared with previous work, our scheme also gains higher security performance by eliminating the participation of third party.