CREMAug 9, 2019

Privacy-Aware Distributed Mobility Choice Modelling over Blockchain

arXiv:1908.03446v22 citations
AI Analysis

This addresses privacy concerns for mobility data users, but it is incremental as it applies existing blockchain and distributed computing methods to a specific domain.

The paper tackles the problem of preserving privacy in distributed mobility choice modeling by introducing a blockchain-based data-market where participants compute locally without sharing raw data, and demonstrates that the estimated model parameters are consistent and reproducible in a case study.

A generalized distributed tool for mobility choice modelling is presented, where participants do not share personal raw data, while all computations are done locally. Participants use Blockchain based Smart Mobility Data-market (BSMD), where all transactions are secure and private. Nodes in blockchain can transact information with other participants as long as both parties agree to the transaction rules issued by the owner of the data. A case study is presented where a mode choice model is distributed and estimated over BSMD. As an example, the parameter estimation problem is solved on a distributed version of simulated annealing. It is demonstrated that the estimated model parameters are consistent and reproducible.

Foundations

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