BELIEVE: Privacy-Aware Secure Multi-Party Computation for Real-Time Connected and Autonomous Vehicles and Micro-Mobility Data Validation Using Blockchain—A Study on New York City Data

Abstract

Connected and autonomous vehicles, as well as micro-mobility devices (e-scooters, e-bikes, and smartphones), constantly generate tremendous amounts of mobility data, comprising spatio-temporal trajectories and other sensory data, the sharing of which can assist in different safety and intelligent transportation system applications. However, constant sharing of such data for real-time mobility decisions could violate the privacy of respective users. At the same time, malicious users could generate and share false data, which would be potentially harmful for stakeholders relying on this data for their safety and mobility decisions. In this paper, we propose a new framework: Blockchain-Enabled Location Identification and Efficient Validation with Encryption” (BELIEVE)—a blockchain-based platform with multi-party computation (MPC)—to securely validate data from a mobility source without violating the user’s privacy. The smart contractin BELIEVE first enables a source to initiate the mobility data validation process, then enables mobile peers in the vicinity to reach a consensus on the data validation using MPC without requiring the source to share raw data, thereby preserving the user’s privacy. The spatio-temporal validation is then updated on a distributed ledger (Inter Planetary File System) as an immutable transaction. Real-time data validation is challenging, considering constant mobility alongside the reduction of resource consumption at the devices and, therefore, to address this, we employ an adaptive approach to the problem where the validation frequency as well as storage on the blockchain are dynamically decided by the nodes, based on the network conditions. We evaluate BELIEVE using a simulation model developed for a portion of New York City, U.S., transportation network and it achieves lower delays and overhead.