Research On Task Assignment Based On Bilateral Privacy Protection In Mobile Crowdsensing

Smartphones have become the most common devices in people’s lives,and are obviously changing the way we live and perceive.Thanks to the rapid development of Internet of things technology,mobile crowdsensing,as a new example of data perception,is gradually emerging.Mobile crowdsensing is a new way of data acquisition that combines crowdsourcing and mobile device perception,Users participating in crowdsensing activities use their smart devices to form a flexible sensor network through ubiquitous wireless networks,which can provide reliable data services for groups or organizations with large-scale data needs.Compared with the traditional fixed deployment sensing mode,mobile crowdsensing has the advantages of wide sensing range,large sensing scale and low maintenance cost.It has a wide application prospect in real-time road traffic monitoring,air and noise pollution,crime control and wildlife monitoring.With the continuous in-depth research in the field of mobile crowdsensing,the problem of privacy disclosure in mobile crowdsensing has attracted more and more attention.Because in the mobile crowdsensing activities,in order to achieve the goal of maximizing its own benefits,the mobile crowdsensing platform will consider the factor of sensing cost when allocating tasks.This paper believes that the sensing cost is the cost of users completing tasks(measured by the distance from users to tasks).Therefore,the platform needs the location information of tasks and workers to allocate tasks,However,this information is undoubtedly sensitive to users.Users’ concerns about the disclosure of privacy information will greatly hinder their enthusiasm to participate in group intelligence perception activities.At present,more and more studies have focused on the work of privacy protection in the field of mobile crowdsensing.However,most of the existing privacy protection work focuses on the protection of workers’ privacy information,but there is little work on the protection of task privacy information,which is not conducive to the long-term development of the whole mobile crowdsensing system.Therefore,how to realize the bilateral privacy protection of workers and tasks in mobile crowdsensing has become the key research problem of this paper.Focusing on the key problem of minimizing the cost of completing the task while still ensuring the privacy and information security of worker and tasks,this paper designs a bilateral privacy protection task allocation method based on matrix multiplication.The specific contents are as follows:To solve the problem of privacy protection,when task publishers publish task information and workers upload their current location information,they use the privacy protection mechanism proposed by us to process the above information,so that the relevant privacy information will not be exposed to the platform and other unrelated individuals;At the same time,aiming at the problem of task allocation,two different task allocation strategies are proposed based on bilateral privacy protection.It also provides a reasonable proof for the proposed bilateral privacy protection method.Finally,we use three actual data sets to carry out several simulation experiments on our proposed task allocation method under bilateral privacy.The experimental results show that compared with other benchmark methods,the proposed method can achieve good task allocation effect and privacy protection effect at the same time.