Dynamic In-Vehicle Message Filtering by Vehicle State
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Solution Overview
Problem
In in-vehicle networks, existing communication devices struggle to accurately detect unauthorized messages due to changes in vehicle states, leading to potential unauthorized data invasions and spoofing attacks, as they do not dynamically adjust filtering rules based on vehicle conditions.
Innovation Solution
A communication device with an acquisition unit for state information, an estimation unit to estimate the vehicle's state, a setting unit to dynamically set filtering rules based on the estimated state, and a filter unit to execute filtering processing, ensuring only authorized messages are transmitted or received, thereby enhancing detection accuracy for unauthorized messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed filtering rules are used for message detection, then the device complexity is reduced, but the detection accuracy for unauthorized messages deteriorates due to inability to adapt to changing vehicle states
Solution Approach 1:
The filtering rule is changed from a static fixed configuration to a dynamic state-dependent configuration. The communication device now determines filtering rules based on the current vehicle state (e.g., running state, stop state), allowing the detection accuracy to adapt to changing conditions while maintaining manageable complexity through state-based rule selection.
Solution Approach 2:
The filtering rule parameters are changed according to vehicle state parameters. Different filtering rules are applied for different vehicle states (running, stopping, etc.), allowing the detection characteristics to be optimized for each specific operational context without requiring a single complex universal rule set.
2Reliability
If state-based dynamic filtering is implemented, then the detection accuracy for unauthorized messages is improved, but the device complexity increases due to additional state monitoring and rule management components
Solution Approach 1:
The filtering mechanism is segmented into state-dependent rule sets. Instead of one monolithic complex filtering system, multiple simpler filtering rules are created for different vehicle states (running state rules, stop state rules, etc.). This segmentation reduces the complexity of individual rule sets while maintaining high detection reliability through appropriate rule selection based on current state.
3Measurement precision
If filtering rules are adjusted according to vehicle state transitions, then false detection rates are reduced, but the loss of time for state monitoring and rule switching increases
Solution Approach 1:
Filtering rules for different vehicle states are predetermined and stored in advance. When a state transition is detected, the appropriate pre-configured rule set can be quickly switched to without requiring real-time analysis or complex rule generation. This preliminary preparation minimizes the time loss associated with rule changes while maintaining low false detection rates.
Data Source
AI summary
A communication device includes: a communication section that transmits and receives a message in a network; an acquisition unit that acquires state information on a state of an object for which the network is provided; an estimation unit that estimates the state of the object based on the state information acquired in the acquisition unit; a setting unit that sets a filtering rule based on the state estimated in the estimation unit; and a filter unit that executes filtering processing for the message in accordance with the filtering rule set in the setting unit.