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The success of dynamic spectrum sharing in wireless networks depends on reliable automated enforcement of spectrum access policies. In this paper, a crowdsourced approach is used to select volunteers to detect spectrum misuse. Volunteer selection is based on multiple criteria, including their reputation, likelihood of being in a region and ability to effectively detect channel misuse. We formulate the volunteer selection problem as a stable matching problem, whereby, volunteers' monitoring preferences are matched to channels' attributes. Given a set of volunteers, the objective is to ensure maximum coverage of the spectrum enforcement area and accurate detection of spectrum access violation of all channels in the area. The two matching algorithms, Volunteer Matching (VM) and Reverse Volunteer Matching (RVM) are based on variants of the Gale-Shapley algorithm for stable matching. We also propose two Hybrid algorithms, HYBRID-VM and HYBRID-RVM that augment the matching algorithms with a Secretary-based algorithm to overcome the shortcomings of the individual vanilla algorithms. Simulation results show that volunteer selection by using HYBRID-VM gives better coverage of region (better by 19.2% when compared to threshold-based Secretary algorithm), better accuracy of detection and better volunteer happiness when compared to the other algorithms that are tested.