针对移动群智感知网络中感知的任务分配以及保护感知用户的隐私信息问题，提出了一种基于用户属性感知的任务分配与隐私保护协同机制。首先，根据感知用户固有属性以及历史任务参与记录，挖掘用户对任务的不同倾向、意愿和访问等来量化出用户的静态属性和社会属性; 然后，将用户属性作为输入，使用 BP 神经网络对用户服务能力进行分析，实现任务与用户的优化分配; 最后，感知用户生成假名参与感知任务，结合环签名对用户属性生成随机数进行属性加密，确保感知用户在隐私安全的前提下，提升平台感知数据的准确程度。仿真实验结果表明，文中所提出的策略能够有效地选择出感知用户，验证了用户上传数据的可用性，保护了用户的身份安全。

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．