Game method for position privacy protection and platform task allocation in mobile crowd sensing

Abstract

The invention provides a game method for position privacy protection and platform task allocation in mobile crowd sensing, which comprises the following steps: firstly, the interaction between users and a platform is simulated through a trusted third party: each user selects a privacy budget to add noise to a position, and the platform allocates a task according to the disturbance position of eachuser; then an interaction process is modeled as a game, and an equilibrium point is derived; different position disturbance strategiesare continuously tried by using a reinforcement learning method,and an optimal position disturbance scheme is output. Experimental results show that the mechanism can improve the overall utility of the user as much as possible while optimizing the task allocationutility, and therefore the user and the platform achieve a win-win situation. According to the method, the problems that in the process that an MCS system needs to provide personalized privacy protection for users to attract more users to participate in tasks, due to the existence of malicious attackers, the privacy protection strength of the users is improved, so that the location availability becomes poor, and the task allocation effectiveness is reduced are solved.

Description

technical field [0001] The technical solution belongs to the field of network technology, and is specifically a win-win game method of (user) location privacy protection and platform task assignment in mobile crowd sensing MCS. Background technique [0002] In recent years, the vigorous development of Internet of Things technology has greatly promoted the popularity of Mobile Crowd Sensing (MCS). A typical MCS system consists of a data requester, a server (MCS platform) and mobile users. The server assigns the task of the data requester to the mobile user in the MCS system, and the mobile user uses the mobile smart device to complete the data collection and send it back to the server and get a certain reward. [0003] Task allocation is one of the most important links in the MCS system. The goal is to optimize the utility of the overall system while accomplishing all (or most) of the tasks in the target perception area. Minimizing travel distance is often chosen as the op...

AI Technical Summary

Problems solved by technology

Due to the strong arbitrariness of the user's choice of privacy budget, especially when there are malicious attackers in the MCS system, the user's choice of a privacy budget with greater privacy protection will reduce the availability of the user's location, which is not conducive to the allocation of tasks on the MCS platform

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