Data transaction method for personalized privacy protection requirement of terminal equipment

Abstract

The invention relates to a data transaction method for a personalized privacy protection demand of terminal equipment. A data transaction platform firstly designs a series of contracts according to budget constraints and privacy preference information of a data owner; each data owner selects a contract from a series of contracts according to a target of optimizing own income and signs the contract with the platform; each data owner processes the original data according to a random perturbation mechanism corresponding to the privacy protection level in the signed contract and then submits the original data to the data transaction platform; the data transaction platform pays for each data owner according to the data transaction price in the signed contract after receiving the data acquired from the data owner; and the data transaction platform adopts an aggregation statistical method for the collected data to obtain an aggregation statistical result and returns the aggregation statistical result to the data consumer who puts forward the demand. And more accurate data can be obtained as much as possible under the condition of meeting personalized privacy constraint and selfish constraint, so that effectiveness optimization of transaction data is realized.

Description

technical field [0001] The invention relates to a data transaction technology oriented to edge intelligence, in particular to a data transaction method oriented to the personalized privacy protection requirements of terminal equipment. Background technique [0002] In recent years, with the rapid development of information technologies such as the Internet of Things, cloud computing, and artificial intelligence, the amount of global data has grown exponentially. According to the forecast of the international authoritative organization Statista, the global data generation volume is expected to reach 2142ZB in 2035, with a compound annual growth rate of nearly 30%, and the global data volume will usher in a larger explosion. In addition to this, the number of connected devices continues to grow steadily. A forecast by IDC estimates that by 2025, there will be 41.6 billion IoT devices worldwide and will generate 79.4ZB of data. These IoT devices are distributed in various plac...

AI Technical Summary

Problems solved by technology

[0006] However, considering the individual privacy requirements of terminal devices and selfish data transaction issues face many technical challenges

First, data privacy protection and data utility maximization are mutually restrictive, and how to balance the two is a thorny issue; second, most current privacy protection mechanisms are based on centralized differential privacy technology, and such solutions are usually Assuming that there is a credible data collector, this assumption still has a large privacy risk, and the communication cost is high; thirdly, after the credible data collector collects the data, it imposes a privacy protection policy on the entire data set, which can be based on the data Users' needs impose different levels of privacy protection policies, but it is difficult to meet the individual privacy protection requirements required by each data owner; fourth, the privacy requirements required by each terminal device are different, and this is their own private information. Other participants or data trading platforms have no way of knowing

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