A privacy-preserving decentralized aggregated ride-sharing platform utilizing blockchain and differential privacy

Abstract

Ride-sharing platforms have emerged as significant components in modern urban mobility providing flexible, cost-effective, and efficient transportation solutions. With a growing user base, these platforms have access to the location data of millions of users and this data can be used in predicting traffic conditions and enhancing the overall ride-sharing experience. However, the traditional ride-sharing platforms rely solely on their own data, overlooking the broader traffic conditions shaped by multiple service providers (SPs), which highlights the need for aggregated systems to get more accurate traffic insight. However, aggregated platforms are vulnerable to critical privacy threats because of their dynamic and interconnected nature, creating a broad attack surface, hence publishing data while ensuring data privacy becomes a significant challenge here. Additionally, traditional ride-sharing platforms rely on centralized systems which are associated with the risk of single points of failure, and potential attacks from malicious participants. To address these limitations, this paper presents a decentralized and privacy-preserving aggregated ride-sharing framework that integrates Blockchain, Differential Privacy (DP), and OAuth-based access delegation. The aggregated platform provides information of all available drivers and active search requests in a specific area, gathered from multiple SPs. The use of blockchain helps to establish an immutable, verifiable, and tamper-resistant control layer for managing users’ metadata, while hashed or encrypted operational data is maintained in an off-chain database for efficiency. DP is used to share location data between SPs and aggregators in an privacy preserving, yet utility-retaining manner, while real data is exchanged only when the user selects a verified SP for booking, ensuring information sharing occurs exclusively within consent-based, OAuth-secured transactions. In this proposal, this research aim to bridge together blockchain with DP and explore it as a novel solution to provide two layers of security and privacy, paving the way for a decentralized and privacy preserving aggregated ride-sharing platform. By showing all SPs’ available drivers and nearby users, this aggregated approach enhances ride-matching efficiency and promotes a more comprehensive and accurate traffic and demand prediction system.