The era of Big Data has brought with it a richer understanding of user
behavior through massive data sets, which can help organizations optimize the
quality of their services. In the context of transportation research, mobility
data can provide Municipal Authorities (MA) with insights on how to operate,
regulate, or improve the transportation network. Mobility data, however, may
contain sensitive information about end users and trade secrets of Mobility
Providers (MP). Due to this data privacy concern, MPs may be reluctant to
contribute their datasets to MA. Using ideas from cryptography, we propose an
interactive protocol between a MA and a MP in which MA obtains insights from
mobility data without MP having to reveal its trade secrets or sensitive data
of its users. This is accomplished in two steps: a commitment step, and a
computation step. In the first step, Merkle commitments and aggregated traffic
measurements are used to generate a cryptographic commitment. In the second
step, MP extracts insights from the data and sends them to MA. Using the
commitment and zero-knowledge proofs, MA can certify that the information
received from MP is accurate, without needing to directly inspect the mobility
data. We also present a differentially private version of the protocol that is
suitable for the large query regime. The protocol is verifiable for both MA and
MP in the sense that dishonesty from one party can be detected by the other.
The protocol can be readily extended to the more general setting with multiple
MPs via secure multi-party computation.

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