A Jointly Differentially Private Scheduling Protocol for Ridesharing Services

Ridesharing services have gained tremendous popularity in recent years, benefiting the traffic and environment of cities to a large extent. However, with the demand of ridesharing services increasing sharply, serious privacy concerns (e.g., users' mobility patterns) of ridesharing have become a major barrier against its further development. In this paper, we study the privacy protection of users' location information in the scheduling of ridesharing services. Based on a state-of-the-art variant of differential privacy, joint differential privacy, we first propose a scheduling protocol for the purpose of protecting users' location privacy and minimizing vehicle miles in the system. Then, in order to obtain a practical solution, we investigate several techniques to enhance the proposed protocol from both the privacy and efficiency aspects. The privacy of the proposed scheduling protocol is rigorously proven. Furthermore, we extensively evaluate our proposal based on a real-world data set. The analysis and experimental results show that the proposed protocol can achieve joint differential privacy, satisfactory scheduling performance, and reasonable efficiency.