Abstract: Aiming at the problems of sensing task allocation and the protection of private information of the sensing user in mobile crowd sensing network，a collaborative mechanism of task allocation and privacy protection based on user attribute awareness was proposed． Firstly，according to the inherent attributes of the sensing user and the his-torical task participation record，the user＇s different tendencies，wishes and access to the task were mined and taken as the indexes to quantify the user＇s static attributes and social attributes． Then，the user attributes were considered as input，and the BP neural network was used to analyze user service capability，so as to realize the optimal alloca-tion of tasks and users． Finally，the sensing user generated pseudonyms to participate in the sensing task，and the random number generated by user attributes was encrypted based on the ring signature． Under the premise of ensu-ring the privacy of the perceived users，the accuracy of the platform＇s perceived data was improved． The simulation experiment results show that the proposed strategy can effectively select the sensing users，validate the availability of the user＇s uploaded data，and protect the user＇s identity security．

Key words: mobile crowd sensing, task allocation, privacy-preserving, attribute encryption