Ridesharing, in which drivers offer to share their rides, allows reduction of travel costs for both drivers and riders; such practice is increasingly popular. Modern ridesharing systems, enhanced with location-based features, have improved user experience by enabling drivers and riders to arrange a trip in near real time. However, the fine-grained nature of location data collected by the service providers and exchanged between users raises privacy issues that could disrupt the adoption of such systems. In this paper, we present SRide: a privacy-preserving protocol for ridesharing that addresses the matching problem for dynamic ridesharing systems. We design and implement a prototype of SRide that operates in four steps. First, it generalizes users spatiotemporal data of users. Next, it relies on a secure filtering protocol to compute feasible matches. Then, it uses an improved version of Priv-2SP-SPa privacy-preserving protocol to compute meeting points for ridesharing-to compute a ridesharing score for each feasible pair. Finally, it computes the optimal assignment of drivers and riders based on their ridesharing scores. We conduct an experimental trace-driven evaluation of the proposed scheme to demonstrate its practical feasibility.