Dynamic Vehicle Data Security Ratings Through AI Multidimensional Scoring
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Solution Overview
Problem
Existing technologies lack a practical way for users to assess and manage the complex and diverse data handling practices in vehicles, including encryption, data retention, authentication, and vulnerabilities, leading to inadequate data security and privacy protection.
Innovation Solution
A system using artificial intelligence and machine learning models generates multi-dimensional data handling scores for vehicles and in-vehicle units, analyzing data handling practices, vulnerabilities, and online news to provide transparent and dynamic security and privacy ratings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional data handling approaches are used in vehicles, then data processing can be performed, but users have no control over security and privacy protection
Solution Approach 1:
The patent implements a feedback mechanism where users receive security and privacy ratings for their vehicles based on analyzed data handling approaches. This feedback loop enables users to understand their current security posture and make informed decisions about data sharing, thereby gaining control over their data security while improving protection through awareness-driven behavior changes.
Solution Approach 2:
The patent introduces an intermediary system that acts as a mediator between vehicle data handling processes and users. This intermediary analyzes data handling approaches, generates security ratings, and presents them to users in an understandable format, bridging the gap between complex technical processes and user decision-making capabilities.
2Adaptability or versatility
If multi-dimensional data handling approaches are used in vehicles, then comprehensive data processing is achieved, but the complexity of assessing security practices increases
Solution Approach 1:
The patent segments the complex assessment of data handling approaches into distinct analytical components. The system evaluates multiple attributes including encryption practices, data retention policies, authentication mechanisms, and vulnerability management separately, then aggregates these into an overall security rating. This segmentation makes the complex assessment process manageable and interpretable for users.
Solution Approach 2:
The patent transforms complex security assessment data into simplified parameter representations through security and privacy ratings. By converting multiple dimensional security attributes into a unified rating system, the patent enables users to comprehend and compare security postures across different vehicles without being overwhelmed by the underlying complexity.
3Ease of operation
If conventional rating technologies are used, then simple ratings can be provided, but they fail to capture the diverse and non-standardized data handling practices in vehicles
Solution Approach 1:
The patent extends conventional one-dimensional rating approaches by introducing multiple dimensions for security and privacy assessment. The system evaluates data handling practices across multiple attributes and dimensions, then synthesizes these into a comprehensive multi-dimensional rating that accurately reflects the complexity of vehicle data handling while remaining accessible to users.
Data Source
AI summary
A data security method includes generating, using artificial intelligence algorithms, at least one machine learning model that is configured to generate scores for multiple attributes of one or more data handling approaches associated with a vehicle and/or an in-vehicle unit. The method further includes analyzing one or more data handling approaches associated with a target vehicle or a target in-vehicle unit. The method further includes generating, using the at least one machine learning model and the one or more data handling approaches that have been analyzed, scores for the multiple attributes of each of the one or more data handling approaches. The method includes processing the scores to generate a data handling score for one or both of the target vehicle or in-vehicle unit. The data handling score includes a security score for one or both of the target vehicle or the in-vehicle unit.