A privacy-preserving spectrum auction scheme using paillier cryptosystem with public verification

2019 ◽  
Vol 36 (5) ◽  
pp. 4215-4226 ◽  
Author(s):  
Jiaqi Wang ◽  
Marimuthu Karuppiah ◽  
Saru Kumari ◽  
Zhiyin Kong ◽  
Wenbo Shi
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mingwu Zhang ◽  
Bingruolan Zhou

Combinatorial auctions can be employed in the fields such as spectrum auction, network routing, railroad segment, and energy auction, which allow multiple goods to be sold simultaneously and any combination of goods to be bid and the maximum sum of combinations of bidding prices to be calculated. However, in traditional combinatorial auction mechanisms, data concerning bidders’ price and bundle might reveal sensitive information, such as personal preference and competitive relation since the winner determination problem needs to be resolved in terms of sensitive data as above. In order to solve this issue, this paper exploits a privacy-preserving and verifiable combinatorial auction protocol (PP-VCA) to protect bidders’ privacy and ensure the correct auction price in a secure manner, in which we design a one-way and monotonically increasing function to protect a bidder’s bid to enable the auctioneer to pick out the largest bid without revealing any information about bids. Moreover, we design and employ three subprotocols, namely, privacy-preserving winner determination protocol, privacy-preserving scalar protocol, and privacy-preserving verifiable payment determination protocol, to implement the combinatorial auction with bidder privacy and payment verifiability. The results of comprehensive experimental evaluations indicate that our proposed scheme provides a better efficiency and flexibility to meet different types of data volume in terms of the number of goods and bidders.


2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Zhaowen Lin ◽  
Xinglin Xiao ◽  
Yi Sun ◽  
Yudong Zhang ◽  
Yan Ma

One of the concerns people have is how to get the diagnosis online without privacy being jeopardized. In this paper, we propose a privacy-preserving intelligent medical diagnosis system (IMDS), which can efficiently solve the problem. In IMDS, users submit their health examination parameters to the server in a protected form; this submitting process is based on Paillier cryptosystem and will not reveal any information about their data. And then the server retrieves the most likely disease (or multiple diseases) from the database and returns it to the users. In the above search process, we use the oblivious keyword search (OKS) as a basic framework, which makes the server maintain the computational ability but cannot learn any personal information over the data of users. Besides, this paper also provides a preprocessing method for data stored in the server, to make our protocol more efficient.


Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1274 ◽  
Author(s):  
Chuan Zhang ◽  
Liehuang Zhu ◽  
Chang Xu ◽  
Xiaojiang Du ◽  
Mohsen Guizani

The explosive number of vehicles has given rise to a series of traffic problems, such as traffic congestion, road safety, and fuel waste. Collecting vehicles’ speed information is an effective way to monitor the traffic conditions and avoid vehicles’ congestion, however it may threaten vehicles’ location and trajectory privacy. Motivated by the fact that traffic monitoring does not need to know each individual vehicle’s speed and the average speed would be sufficient, we propose a privacy-preserving traffic monitoring (PPTM) scheme to aggregate vehicles’ speeds at different locations. In PPTM, the roadside unit (RSU) collects vehicles’ speed information at multiple road segments, and further cooperates with a service provider to calculate the average speed information for every road segment. To preserve vehicles’ privacy, both homomorphic Paillier cryptosystem and super-increasing sequence are adopted. A comprehensive security analysis indicates that the proposed PPTM can preserve vehicles’ identities, speeds, locations, and trajectories privacy from being disclosed. In addition, extensive simulations are conducted to validate the effectiveness and efficiency of the proposed PPTM scheme.


2019 ◽  
Vol 26 (5) ◽  
pp. 142-150 ◽  
Author(s):  
Yanjiao Chen ◽  
Zhuo Ma ◽  
Qian Wang ◽  
Jing Huang ◽  
Xin Tian ◽  
...  

2015 ◽  
Vol 26 (5) ◽  
pp. 1393-1404 ◽  
Author(s):  
He Huang ◽  
Xiang-Yang Li ◽  
Yu-e Sun ◽  
Hongli Xu ◽  
Liusheng Huang

2021 ◽  
pp. 100037
Author(s):  
Ruinian Li ◽  
Tianyi Song ◽  
Bo Mei ◽  
Chunqiang Hu ◽  
Wei Li ◽  
...  

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