A Secure Truth Discovery for Data Aggregation in Mobile Crowd Sensing

With the rapid development of portable mobile devices, crowd sensing systems (MCS) have been widely studied. However, data provided by participants in MCS applications is always unreliable, which affects service quality system, and truth discovery technology can effectively obtain true values from multiple users. At same time, privacy leaks also restrict users’ enthusiasm for participating MCS. Based on this, our paper proposes a secure aggregation systems, STDDA, iteratively calculates user weights to real object data. In order protect data, STDDA divides users into several clusters, clusters ensure adding secret random numbers perceived cluster head node uses sum protocol result sense uploads it server so that cannot weight individual users, further ensuring user’s weight. addition, using method, provides corresponding processing mechanisms dynamic joining exiting, enhances robustness system. Experimental results show has characteristics high accuracy, low communication, security.