Differential Privacy-Based Double Auction for Data Market in Blockchain-Enhanced Internet of Things. (21st June 2022) - Zhang, Junhua
Abstract : With the rapid development of the Internet of Things (IoT), large amounts of data are collected, which constitute a valuable business resource. Hence, a suitable IoT data market needs to be established, and the provision of safe and effective trading services for multiple buyers and sellers is required. This paper introduces an IoT data market framework supported by blockchain. It focuses on a transaction realization scheme for multiple buyers and sellers. In the scheme, the mechanisms are designed to determine the corresponding data providers and recipients for the buyers and sellers, respectively, and the transaction prices of both parties. When the data market runs, an inference attack will raise bid information leakage issues. We study a transaction scheme that enables differential privacy protection of bids based on an exponential mechanism. This paper theoretically proves the individual rationality, weak budget balance, and truthfulness of the normal transaction scheme and differential privacy-based transaction scheme. This paper also theoretically proves the effectiveness of the differential privacy protection for bids of transaction participants. Furthermore, this paper verifies the performances of the two schemes through digital simulation experiments. From the experiments, we can also prove that these schemes occupy reasonable social welfare and computational overhead.