In-Vehicle Message Anomaly Checks for Limited Execution Time
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Solution Overview
Problem
Existing methods for detecting anomalous messages in in-vehicle networks are inadequate as they often fail to perform anomaly detection processes effectively due to short detection processing times.
Innovation Solution
An anomaly detection method and device that select and execute appropriate anomaly determination functions based on available execution time, load amount, data amount, and total number of messages, utilizing combinations of anomaly determinations including reception timing, message fields, and periodicity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive anomaly detection processes are performed on all messages, then detection accuracy is improved, but processing time increases and may exceed available detection processing time
Solution Approach 1:
The anomaly detection process is divided into multiple determination functions (first determination function, second determination function, third determination function) that can be selectively executed. Each function analyzes different aspects of messages (e.g., reception timing, message ID, data content), allowing the system to perform comprehensive detection when time permits while enabling selective execution when time is limited.
Solution Approach 2:
The system dynamically selects which determination functions to execute based on the available detection processing time. When detection processing time is sufficient, more comprehensive functions are executed; when time is limited, only essential functions are performed. This dynamic adaptation resolves the contradiction between detection accuracy and processing time.
2Reliability
If multiple determination functions are executed to improve detection reliability, then anomaly detection reliability is improved, but device complexity and processing overhead increase
Solution Approach 1:
The anomaly determination device incorporates multiple determination functions that can operate independently or in combination. These functions analyze different message attributes (reception timing, message ID, data content) using a unified framework, allowing the system to achieve high reliability through multi-faceted analysis without proportionally increasing overall system complexity.
Data Source
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AI summary
In an anomaly determination method for determining an anomaly in a received message, a plurality of messages which include messages that are periodic and each of which includes a first field having a fixed value and a second field having a variable value are each received as the received message, and one of a plurality of combinations to be used for determination each of which includes at least one of a plurality of anomaly determinations including an anomaly determination utilizing a reception timing based on the periodicity or the number of received messages, an anomaly determination utilizing the first field, and an anomaly determination utilizing the second field, is selected according to one or more criteria among available execution time of the anomaly determination method, a load amount, a data amount, and the number of messages (S1103).