Vehicle Kinematic Data Encryption for Confidential Driving Style Analysis
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Solution Overview
Problem
Existing methods for processing vehicle kinematic data for services like personalized insurance and diagnostics lack scalability, flexibility, and do not adequately protect the confidentiality of sensitive driver data, particularly in light of GDPR regulations.
Innovation Solution
A method involving symmetric encryption and homomorphic encryption is used to encrypt and process vehicle data externally, allowing classification of driving styles without revealing raw data to service providers, using a computing platform to perform processing in the homomorphic domain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vehicle data is transmitted to service providers for processing, then services like personalized insurance and diagnostics can be provided, but data confidentiality and privacy protection are compromised
Solution Approach 1:
The system performs preliminary encryption of vehicle data before transmission to service providers. The homomorphic encryption is applied in advance, allowing data to be processed in encrypted form, thus preventing unauthorized access to raw data while enabling service delivery.
Solution Approach 2:
The patent introduces an intermediary encryption layer using homomorphic encryption properties. This intermediary mechanism allows service providers to process data without directly accessing the raw information, acting as a mediator that preserves confidentiality while enabling computation.
2Object-affected harmful factors
If individual vehicles process data locally using privacy-preserving methods, then data confidentiality is maintained, but scalability and flexibility are reduced
Solution Approach 1:
The system uses universal homomorphic encryption keys that can be applied across multiple vehicles and service providers. The encryption scheme is designed to work universally, allowing any service provider with the appropriate keys to process data from any vehicle, thus achieving scalability and flexibility simultaneously.
Solution Approach 2:
The patent employs cryptographic key copying and distribution mechanisms where encryption keys can be securely distributed to multiple service providers. This allows the same confidentiality protection to be copied and applied across different service providers without requiring individual vehicle processing capabilities.
3Adaptability or versatility
If service providers access raw vehicle data for processing, then processing flexibility and service customization are improved, but GDPR compliance and privacy protection are compromised
Solution Approach 1:
Data is encrypted before leaving the vehicle, performing the privacy protection action in advance. This preliminary encryption ensures that even when service providers access and process the data, they only handle encrypted information, thus maintaining GDPR compliance while preserving processing flexibility.
Solution Approach 2:
Homomorphic encryption serves as an intermediary layer between the vehicle data and service provider processing. This intermediary mechanism allows service providers to perform flexible processing operations on encrypted data without directly accessing raw information, ensuring both GDPR compliance and processing flexibility.
4Adaptability or versatility
If multiple service providers need to process vehicle data, then service variety increases, but individual communication and processing coordination becomes complex
Solution Approach 1:
The system establishes a universal communication protocol based on homomorphic encryption that works across multiple service providers. All providers use the same encryption scheme and key distribution mechanism, simplifying coordination while supporting diverse service offerings.
Solution Approach 2:
Encryption keys and processing protocols can be copied and distributed to multiple service providers uniformly. This copying approach allows any number of service providers to access and process vehicle data using the same standardized mechanism, reducing communication complexity while enabling service variety.
Data Source
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AI summary
The present invention concerns a method for confidentially processing the kinematic data of a vehicle (210), in particular a method for classifying this data in order to determine the driving style of the vehicle while respecting the confidentiality of the data in question. The data is encrypted (254) by the vehicle by means of a symmetric encryption algorithm using a secret key generated (251) by the vehicle. This secret key is encrypted (252) by the vehicle by means of a homomorphic asymmetric encryption algorithm by using the public key of a vehicle service provider (240). The data encrypted by means of the secret key, and the homomorphically encrypted secret key, are transmitted (253, 255) by the vehicle to an access point that transcrypts (261) them and transmits (262) the homomorphically encrypted data to a calculation platform (230). The platform performs (271) the confidential processing operation in the homomorphic domain and transmits (272) the homomorphically encrypted results to the server of the vehicle service provider (240).