Vehicle Data Anonymization Using De-Identified VINs
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Solution Overview
Problem
Existing vehicle data collection systems fail to adequately protect individual privacy, particularly in the context of vehicle-generated data from ADAS and autonomous driving systems, and face challenges in complying with privacy regulations like GDPR, while also lacking efficient methods for anonymizing and managing such data for statistical analysis.
Innovation Solution
A centralized system that anonymizes vehicle-generated data by converting vehicle identification numbers (VINs) into de-identified versions, storing this data in a neutral server independent of manufacturers, and allowing reconstruction of relationships with owner consent or legal orders, while enabling statistical analysis without compromising privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If vehicle data is collected and stored centrally for statistical analysis and service improvement, then data utility and analytical value are improved, but privacy protection and security risks deteriorate
Solution Approach 1:
The patent extracts personally identifiable information (PII) such as VINs and driver information from vehicle data before centralization, separating identifiable data from anonymized data. This extraction allows the system to retain useful vehicle operational data for statistical analysis while removing privacy-sensitive elements, thus resolving the contradiction between data utility and privacy protection.
Solution Approach 2:
The patent introduces an intermediary anonymization process that acts as a mediator between raw vehicle data and centralized storage. This intermediary layer transforms identifiable data into anonymized form through techniques like pseudonymization and aggregation, enabling centralization for analytical purposes while maintaining privacy protection as required by GDPR and other regulations.
2Manufacturing precision
If detailed vehicle operational data is collected for verifying and improving ECU and sensor functions, then manufacturing precision and product quality are improved, but data complexity and management burden increase
Solution Approach 1:
The patent segments vehicle data into distinct categories including EDR data, sensor data, ECU operational data, and driver behavior data. This segmentation allows each data type to be managed separately with appropriate processing and storage methods, reducing overall management complexity while preserving the detailed information needed for verifying ECU and sensor functions.
Solution Approach 2:
The patent applies parameter changes by transforming raw vehicle data into standardized formats with consistent schemas and metadata structures. This standardization reduces data management complexity by enabling uniform processing, storage, and analysis across different vehicle types and data sources, while maintaining the precision needed for component verification.
3Object-affected harmful factors
If vehicle data is anonymized for privacy protection, then privacy protection is improved, but data reconstructability and traceability deteriorate
Solution Approach 1:
The patent applies preliminary action by establishing a controlled access framework before data anonymization occurs. This framework pre-defines authorized entities (vehicle manufacturers, regulatory agencies, law enforcement) and their respective access rights, ensuring that while data is anonymized for privacy protection, authorized parties can still retrieve and reconstruct data when legally or contractually permitted through predetermined procedures.
Solution Approach 2:
The patent inverts the traditional approach by maintaining the ability to reconstruct anonymized data under controlled conditions rather than requiring full identifiability from the start. This inversion allows the system to prioritize privacy protection through anonymization while preserving traceability and reconstructability for authorized entities through cryptographic methods and controlled access mechanisms.
Data Source
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AI summary
A system for collecting and managing vehicle-generated data from a vehicle utilizes the vehicle-generated data that is anonymized into a de-identified version of a vehicle identification number (VIN) of an associated vehicle. The de-identified version of the VIN facilitates statistical analysis of the vehicle-generated data without raising issues with regard to privacy of individuals. The anonymized vehicle-generated data can be held in a neutral data server, which is administered by an operator independent of vehicle manufacturers, and provided to a third party.