Vehicle Data PII Filtering via Location-Based Policy
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Solution Overview
Problem
Existing solutions for filtering personally identifiable information (PII) from vehicle data fail to comply with varying privacy regulations across regions, as they are user-dependent and lack automated enforcement mechanisms.
Innovation Solution
A method and system that determine a vehicle's location and apply a region-specific enforcement policy to filter PII objects, using encryption keys to redact sensitive data on-board, ensuring compliance with regional privacy laws and allowing authorized access to original data when required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If user-dependent PII filtering solutions are used, then implementation flexibility is maintained, but compliance with regional privacy regulations cannot be ensured
Solution Approach 1:
The system dynamically adapts PII filtering behavior based on geographic location. Enforcement policies are automatically selected and applied according to the vehicle's current region, enabling the system to comply with different regional privacy regulations without manual reconfiguration. This dynamic adaptation resolves the contradiction by maintaining implementation flexibility through automated policy selection while ensuring reliability through location-specific compliance enforcement.
Solution Approach 2:
The system performs self-service by automatically determining its location, selecting the appropriate enforcement policy, and applying the correct filtering rules without requiring user intervention. This self-service mechanism ensures that the system consistently complies with regional regulations while maintaining flexibility in adapting to different jurisdictions, resolving the contradiction between user-dependent implementation and reliable compliance.
2Loss of information
If all collected vehicle data is stored and transmitted, then data availability for potential uses is maximized, but privacy protection and regulatory compliance are compromised
Solution Approach 1:
The system applies different quality levels of data processing based on location-specific enforcement policies. In regions with strict privacy regulations, PII is filtered or redacted before storage and transmission. In regions with different requirements, less filtering may be applied. This local quality approach maximizes data availability where permitted while protecting privacy where required, resolving the contradiction between data availability and privacy protection.
Solution Approach 2:
The system segments data into PII and non-PII categories, applying different storage and transmission rules to each segment based on the applicable enforcement policy. This segmentation allows the system to maintain maximum availability of non-sensitive data while protecting sensitive information, thereby resolving the contradiction between data availability and privacy protection.
3Device complexity
If PII filtering is performed manually by users, then system complexity is minimized, but automation and consistent regulatory compliance are reduced
Solution Approach 1:
The system performs preliminary action by pre-configuring enforcement policies for different regions and automatically selecting and applying the appropriate policy based on location. This preliminary setup eliminates the need for complex real-time decision-making logic during operation, maintaining relatively simple system architecture while achieving high levels of automation in PII filtering, thus resolving the contradiction between system complexity and automation extent.
Data Source
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AI summary
As vehicles collect more data in autonomous or semi-autonomous operation, the collected data such as video, navigation and telemetry data, can containing personally identifiable information (PII). The PII may be governed by specific handling requirements or privacy policies. In order to comply with these requirements and policies a method, system and computer readable memory are provided for determining a location of a vehicle to enable determination of an enforcement policy associated with the location of the vehicle. The enforcement policy defines one or more PII objects that are to be filtered from the vehicle data. The PII objects contained within the vehicle data can then be filtered such that the PII objects are not identifiable. The filtered data can then be stored or transmitted to a remote location.