Privacy Preserving Data Storage for MaaS Travel Analysis
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Solution Overview
Problem
Current data storage methods for mobility-as-a-service (MaaS) transportation services face challenges in analyzing travel behavior due to the inability to associate personal user information across different service providers, as GDPR regulations prevent storing personal data on blockchain, limiting personalized data analytics and context-based analysis.
Innovation Solution
A privacy-preserving data storing method that separates user identification from trip information, using a first database for user IDs and a second database for trip information, both linked by a unique trip ID, allowing analysis while maintaining user privacy by storing user IDs locally and trip information on a shared blockchain, utilizing data processing circuitry to associate entries for analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If personal user information is stored on blockchain for trip analysis, then data analytics capability is improved, but data protection compliance deteriorates
Solution Approach 1:
The system segments user information into two distinct parts: personal identifiers (user IDs) stored in private databases and trip information stored on the blockchain. This segmentation allows trip data to be shared and analyzed across multiple service providers while personal identifiers remain protected in local databases, resolving the contradiction between analytics capability and data protection compliance.
Solution Approach 2:
The patent introduces trip IDs as intermediary identifiers that link trip information on the blockchain to user IDs in private databases without exposing personal information. These trip IDs act as mediators that enable data association and analysis while maintaining a privacy barrier, allowing analytics without direct access to personal user information.
2Object-affected harmful factors
If user IDs are stored separately in private databases, then user privacy is protected, but ability to associate trips across service providers deteriorates
Solution Approach 1:
Trip IDs serve as intermediary identifiers that enable association of trips across different service providers without requiring direct access to user IDs. The trip IDs are stored on the blockchain and linked to user-specific trips, allowing data processing circuitry to associate multiple trips belonging to the same user while maintaining privacy protection through the intermediary layer.
Solution Approach 2:
The trip ID serves multiple functions: it uniquely identifies a trip, links trip information on the blockchain to user data in private databases, and enables cross-service-provider trip association. This multi-functionality allows the system to maintain privacy while achieving comprehensive trip analysis capabilities.
3Adaptability or versatility
If trip information is stored on shared blockchain, then data sharing across service providers is improved, but data structure complexity increases
Solution Approach 1:
The system segments data storage into two distinct structures: a simplified blockchain structure containing only trip information and trip IDs, and separate private databases containing user identifiers. This segmentation reduces the complexity of the blockchain data structure while enabling comprehensive data sharing through the coordinated use of both storage systems.
Data Source
AI summary
The present disclosure relates to a privacy preserving data storing method, in particular for analyzing a travel behavior of one or more users of mobility-as-a-service (MaaS) transportation services. The method comprises storing at least one user identification, user ID, identifying the one or more users on a trip together with a trip identification, trip ID, identifying the trip in a database entry of a first database and storing trip information on the trip with the trip ID in a database entry of a separate second database. The method further provides for associating the database entries of the first and second databases associated with the same trip ID for an analysis of the travel behavior of the users based on the associated database entries of the first and the second database.