Electronic Control Unit Abnormality Detection Buffer Filtering
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Solution Overview
Problem
Current in-vehicle network intrusion detection systems face high software and hardware processing loads due to the need for monitoring all data frames received by electronic control units for abnormality detection, which is inefficient and resource-intensive.
Innovation Solution
An electronic control unit is designed with a receiver, buffer, writer, first abnormality determiner, reader, and second abnormality determiner to temporarily store data frames and perform abnormality detection only on frames not initially determined as abnormal, reducing processing load by using a buffer for initial determination and applying resource-intensive detection methods only to non-abnormal frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data frames are monitored for abnormality detection, then detection reliability is improved, but processing load increases
Solution Approach 1:
The abnormality detection process is segmented into two stages: first, a simple buffer-based filtering mechanism that compares data frame reception intervals against predetermined thresholds to identify obviously abnormal frames; second, a more sophisticated detection algorithm applied only to frames that pass the initial filter. This segmentation reduces the processing load on the second stage while maintaining detection reliability for both obvious and subtle abnormalities.
Solution Approach 2:
The buffer stores incoming data frames and their reception intervals before detailed analysis, performing preliminary sorting and threshold comparison. This preliminary action prepares the data in advance, allowing the main detection algorithm to operate on pre-processed information, thereby reducing the overall processing load while maintaining detection accuracy.
2Measurement precision
If resource-intensive detection methods are applied to all frames, then detection precision is improved, but processing time increases
Solution Approach 1:
Different detection methods with varying levels of complexity are applied to different data frames based on their characteristics. Frames that exhibit obvious abnormal patterns (such as severely deviating reception intervals) are handled by simple threshold comparison, while only frames requiring nuanced analysis undergo resource-intensive detection. This local differentiation optimizes both precision and processing time.
Solution Approach 2:
The system applies full resource-intensive detection only to the necessary subset of frames that are not clearly normal or clearly abnormal, rather than applying it to all frames. This partial action approach maintains detection precision for critical cases while significantly reducing overall processing time by avoiding redundant intensive analysis of obviously normal frames.
Data Source
AI summary
An electronic control unit includes a receiver that receives a data frame transmitted at given transmission periods from a transmission source electronic control unit connected via a communication network, a buffer capable of storing the data frame, a writer that writes the data frame received by the receiver into the buffer, and an abnormality determiner that determines that the data frame is abnormal when the number of data frames written into the buffer exceeds a given threshold or when the data frame is written in excess of a capacity of the buffer.