Differential privacy in intelligent transportation systems

In this paper, we investigate how the concept of differential privacy can be applied to Intelligent Transportation Systems (ITS), focusing on protection of Floating Car Data (FCD) stored and processed in central Traffic Data Centers (TDC). We illustrate an integration of differential privacy with privacy policy languages and policy-enforcement frameworks like the PRECIOSA PeRA architecture. Next, we identify differential privacy mechanisms to be integrated within the policy-enforcement framework and provide guidelines for the calibration of parameters to ensure specific privacy guarantees, while still supporting the level of accuracy required for ITS applications. We also discuss the challenges that the support of user-level differential privacy presents and outline a potential solution. As a result, we show that differential privacy could be put to practical use in ITS to enable strong protection of users' personal data.