A linkable signature scheme supporting batch verification for privacy protection in crowd-sensing

The maturity of 5G technology has enabled crowd-sensing services to collect multimedia data over wireless network,so it has promoted the applications of crowd-sensing services in different fields,but also brings more privacy security challenges,the most commom which is privacy leakage.As a privacy protection technology combining data integrity check and identity anonymity,ring signature is widely used in the field of privacy protection.However,introducing signature technology leads to additional signature verification overhead.In the scenario of crowd-sensing,the existing signature schemes have low efficiency in multi-signature verification.Therefore,it is necessary to design an efficient multi-signature verification scheme while ensuring security.In this paper,a batch-verifiable signature scheme is proposed based on the crowd-sensing background,which supports the sensing platform to verify the uploaded multiple signature data efficiently,so as to overcoming the defects of the traditional signature scheme in multi-signature verification.In our proposal,a method for linking homologous data was presented,which was valuable for incentive mechanism and data analysis.Simulation results showed that the proposed scheme has good performance in terms of security and efficiency in crowd-sensing applications with a large number of users and data.

Research on Crowdsourcing Price Game Model in Crowd Sensing

Crowd-Sensing is an innovative data acquisition method that combines the perception of mobile devices with the idea of crowdsourcing.It is a new application mode under the development of the Internet of Things.The perceptual data that mobile users can provide is limited.Multiple crowdsourcing parties will share this limited data,but the cost that the crowdsourcing party can pay is limited,and enough mobile users are needed to complete the perceptual task,making the group wisdom is really played.In this process,there is bound to be a game between the crowds and the mobile users.Most of the existing researches consider a group-aware system.A group of mobile users will directly share or compete for the opportunity of the crowd-holders to do tasks and get paid,the behavior of multiple crowd-source parties,and their bilateral interaction with mobile users.The research is not clear enough and there is no targeted research.This paper will model and analyze the dynamic evolution process of crowd sensing perception.Based on the unique characteristics of crowd-source non-cooperative game and crowd-sourced Nash equilibrium,we will develop a perceptual plan for mobile users and use the stability analysis of iterative algorithms to explore a way to better match the capabilities of mobile users and the needs of crowdsourced parties.Our theoretical analysis and simulation results verify the dynamic evolution model of crowdsourcing in group perception and propose a method to improve the efficiency of crowdsourcing.