In-Vehicle Message Anomaly Checks With Adaptive Function Selection
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Solution Overview
Problem
Existing methods for detecting anomalous messages in in-vehicle networks, such as those described in PTL 1, face challenges in performing effective anomaly detection within a short time frame, leading to incomplete or inefficient detection processes.
Innovation Solution
An anomaly determination method that selects from various combinations of anomaly determination functions based on available execution time, load amount, data amount, and total number of messages, utilizing fields with fixed and variable values, and reception timing, to perform appropriate anomaly detection within limited processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive anomaly determination functions are applied, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The system dynamically selects and combines anomaly determination functions based on real-time message characteristics and system state. Different combinations of determination functions are applied to different message types, allowing the system to optimize between detection accuracy and processing speed adaptively rather than using a fixed comprehensive approach for all messages.
Solution Approach 2:
The anomaly determination process is divided into multiple independent determination functions that can be selectively applied. Each function checks specific aspects of messages (e.g., timing, format, content), and the system segments the overall detection process into these modular functions that can be combined based on processing time availability and message characteristics.
2Reliability
If multiple anomaly determination functions are combined, then detection reliability is improved, but device complexity increases
Solution Approach 1:
The system uses dynamic function combination where the set of anomaly determination functions applied to a message depends on the message's characteristics and current system state. This reduces the effective complexity for any single message while maintaining high reliability through comprehensive coverage across different message types.
Solution Approach 2:
The anomaly determination device is designed with multi-functional capability to execute various determination functions selectively. A single device structure handles diverse anomaly detection scenarios by configuring different combinations of determination functions, avoiding the need for separate specialized devices for each function.
Data Source
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.