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A Privacy-Preserving Online Reverse Multi-attributes Auction Scheme Based on Degree-Matching

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Cloud Computing and Security (ICCCS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10039))

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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.

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Acknowledgement

The authors thank the editors and the anonymous reviewers for their valuable comments. This research was supported by National Natural Science Foundation of China (Nos. 61472074, 61401083), the Doctoral Fund of Northeastern University of Qinhuangdao (Grant No. XNB201410); the Fundamental Research Funds for the Central Universities (Grant No. N130323005, L1523009); the Natural Science Foundation of Hebei Province of China (Grant No. F2014501139, F2015501122); the Doctoral Scientific Research Foundation of Liaoning Province (Grant No. F201501143).

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Correspondence to Wenbo Shi .

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Ma, M., Gao, J., Lu, N., Shi, W. (2016). A Privacy-Preserving Online Reverse Multi-attributes Auction Scheme Based on Degree-Matching. In: Sun, X., Liu, A., Chao, HC., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2016. Lecture Notes in Computer Science(), vol 10039. Springer, Cham. https://doi.org/10.1007/978-3-319-48671-0_38

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  • DOI: https://doi.org/10.1007/978-3-319-48671-0_38

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