CAN Bus Signal Waveform Feature Analysis for Abnormality Detection
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Solution Overview
Problem
Current technologies face challenges in accurately detecting abnormalities in CAN bus networks within in-vehicle systems, particularly in identifying minute changes or unauthorized connections without complex configurations or disrupting network operations.
Innovation Solution
A detection device and method that measure and calculate various feature amounts of signal waveforms transmitted over the CAN bus, using a measurement unit, calculation unit, and detection unit to identify abnormalities based on these features, without the need for external pulse signal generators or stopping network communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If TDR technology is used to detect unauthorized connections by observing impedance, then detection capability is improved, but the system requires external pulse signal generators and stops network communication, increasing device complexity and reducing productivity
Solution Approach 1:
The detection device utilizes the CAN bus network's own communication signals for detection purposes. The measurement unit measures signal waveforms of frames already transmitted in the CAN bus, eliminating the need for external pulse signal generators. This self-service approach allows the system to detect abnormalities using its existing operational signals rather than requiring separate detection signals.
Solution Approach 2:
The detection process operates continuously without interrupting CAN bus communication. The measurement unit measures signal waveforms during normal network operation, and the detection unit detects abnormalities based on these measurements while communication continues. This eliminates the need to stop network communication for detection, maintaining continuous useful action.
2Measurement precision
If multiple feature amounts are calculated from signal waveforms, then detection accuracy is improved, but calculation complexity increases
Solution Approach 1:
The detection process is segmented into distinct functional units: a measurement unit that measures signal waveforms, a calculation unit that calculates multiple kinds of feature amounts from the measured waveforms, and a detection unit that detects abnormalities based on these feature amounts. This segmentation allows complex calculations to be performed in a structured manner, managing complexity through modular organization.
Solution Approach 2:
The calculation unit calculates multiple kinds of feature amounts (parameters) from the signal waveforms, such as amplitude, duration, and other characteristics. By extracting and analyzing multiple parameters simultaneously, the system achieves high detection accuracy without requiring complex single-parameter analysis, distributing the computational task across multiple simpler parameter calculations.
Data Source
AI summary
A detection device to be used in an in-vehicle network including a CAN (Controller Area Network) bus and a plurality of function units connected to the CAN bus includes: a measurement unit configured to measure a signal waveform of a frame transmitted in the CAN bus; a calculation unit configured to calculate a plurality of kinds of feature amounts of the signal waveform measured by the measurement unit; and a detection unit configured to detect an abnormality regarding the CAN bus, based on each of the feature amounts calculated by the calculation unit.