Vehicle Information Access Filtering for Privacy-Aware Data Sharing
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Solution Overview
Problem
Existing systems lack a fine-grained access control mechanism for vehicle-associated information, often resulting in either excessive exposure or insufficient provision of data, which can compromise privacy and security.
Innovation Solution
The implementation of a vehicle-associated information filtering engine that uses access control rule information to determine and enforce permissions for accessing vehicle-associated information, allowing for granular control based on various criteria such as entity identity, vehicle motion, and location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If access control rules are implemented to restrict vehicle-associated information, then data privacy and security are improved, but the complexity of the access control system increases
Solution Approach 1:
The access control system segments information access into multiple hierarchical levels: information types (e.g., location, biometric data), entities (internal/external), and access levels (full, partial, none). This segmentation allows granular control without requiring a completely complex monolithic system, as each dimension can be managed independently through structured data formats like JSON policies.
Solution Approach 2:
The patent introduces an intermediary access control mechanism that sits between data sources and requesting entities. This intermediary evaluates access requests against predefined policies and rules, mediating between the need for security and the desire for system simplicity. The intermediary translates complex security requirements into manageable policy evaluations.
2Loss of information
If granular access control is implemented, then information exposure is reduced, but the difficulty of managing access permissions increases
Solution Approach 1:
The system changes the parameters of access control from binary (yes/no) to multi-dimensional, incorporating information type, entity identity, and access level as separate controllable parameters. This allows granular control over what information is exposed while managing complexity through structured parameter evaluation rather than unmanageable permission lists.
Solution Approach 2:
The access control mechanism is designed as a universal system that handles multiple information types, entities, and access scenarios through a single unified policy framework. Rather than creating separate permission systems for different data types or entities, one multi-functional access control mechanism manages all access requests consistently.
3Productivity
If all vehicle-associated information is provided to entities, then operational efficiency is improved, but privacy risks increase
Solution Approach 1:
The system applies local quality by providing different levels and types of information access to different entities based on their specific needs and authorization levels. Rather than uniform information distribution, each entity receives precisely the information quality and quantity appropriate to its function, maintaining operational efficiency while reducing unnecessary privacy exposure.
Data Source
AI summary
In some examples, a system receives vehicle-associated information from a data source associated with a vehicle, and restricts access to the vehicle-associated information based on at least one privacy criterion selected from among a machine learning use criterion relating to use of the vehicle-associated information by a machine learning model, a vehicle motion criterion relating to a movement status of the vehicle, or a person identity criterion relating to an identity of a person in the vehicle.