Mobile crowdsensing (MCS) enables a group of mobile participants to use their intelligent sensing devices to complete the sensing tasks proposed by the task requester. The sensing data users submit is an important factor affecting the effectiveness of sensing task results. How to fairly incentivize users while protecting their privacy is an urgent problem that needs to be solved. Distributing user rewards based on data quality is the mainstream method for achieving fair incentives. However, most current work only uses a subjective approach to weigh different factors in data quality evaluation. Therefore, this paper proposes a fair and privacy-preserving incentive mechanism (FPIM) scheme based on data quality evaluation in MCS. Specifically, we introduce the entropy weight method into the MCS task to achieve objective weighting in secure data quality evaluation protocol by designing new secure interval determination protocol (SIDP) and secure compare protocol (SCP). Experimental results show that the computational cost and communication overhead of the proposed protocols are reduced by about 33% and 25% when compared with the existing schemes.