Vehicle Content Verification with Adaptive Hash Checking
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Solution Overview
Problem
In autonomous driving systems, there is a risk of cyber attacks through unauthorized spoofing terminals, and verifying large-size content data such as map data takes too long, making real-time use of the data impossible.
Innovation Solution
A verification method that divides content data into partial data, generates hash values, and uses a subset of these values along with a signature to quickly verify the content data based on vehicle state and processing power, ensuring security and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the whole content data is verified, then the security is improved, but the verification time increases
Solution Approach 1:
The content data is divided into multiple pieces of partial data, and hash values are generated for each piece. Instead of verifying the entire content data at once, the system verifies a selectively determined number of hash values based on vehicle state information, thereby segmenting the verification process to reduce time while maintaining security
Solution Approach 2:
The system performs partial verification by selectively determining how many hash values to verify based on vehicle state information. When the vehicle is in a safe state, fewer hash values are verified (partial action), while when the vehicle is in an unsafe state, more hash values are verified (excessive action), thus adapting the verification extent to the situation
2Productivity
If the content data is verified in real time, then the productivity is improved, but the measurement precision of data validity decreases
Solution Approach 1:
The verification process is made dynamic by selectively determining the number of hash values to verify based on vehicle state information. The system adjusts the verification depth dynamically - using fewer hash values when the vehicle state is safe (allowing faster real-time processing) and more hash values when the state is unsafe (improving detection accuracy), thus balancing productivity and measurement precision adaptively
Data Source
AI summary
A method for verifying content data to be used in a vehicle is provided. The method includes acquiring content data, acquiring, from partial data divided from the content data, a respective plurality of first hash values, acquiring a signature generated by using the first hash values and a key, acquiring state information that indicates a state of a vehicle, determining an integer N that is greater than or equal to one based on the acquired state information, generating, from N pieces of partial data included in the partial data, respective second hash values, verifying the content data by using each of (a) a subset of the plurality of first hash values respectively generated from partial data other than the N pieces of partial data, (b) the second hash values, and (c) the signature, and outputting information that indicates a result of the verifying.


