Vehicle Message Validation for Malware Interception Detection
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Solution Overview
Problem
Modern automotive systems are vulnerable to malware attacks due to their complex environments and multiple communication channels, lacking a system or method to automatically, dynamically, and proactively shield and protect components from such threats.
Innovation Solution
A method is implemented to detect malware by initiating mock transactions, comparing response messages with predefined indicators, and determining message interception through attributes or content analysis, using an agent within the system to identify and intervene in suspicious communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If components in a vehicle communicate with external entities over the Internet, then the system gains enhanced functionality and connectivity, but the system becomes vulnerable to malware attacks and message manipulation
Solution Approach 1:
The system performs preliminary validation of external entities before allowing communication. It proactively initiates mock transactions to verify the legitimacy of external entities and validates message attributes in advance, preventing malware attacks before they can compromise the system
Solution Approach 2:
The system introduces an intermediary validation layer that mediates between internal components and external entities. This intermediary verifies message attributes, validates external entities through mock transactions, and filters out malicious messages before they reach internal components
2Reliability
If the system implements comprehensive message validation and mock transactions, then security against malware is improved, but system complexity and computational overhead increase
Solution Approach 1:
The system applies different validation strategies to different message types and communication scenarios. It validates critical messages with higher security measures while using lighter validation for less sensitive communications, optimizing the balance between security and complexity
Solution Approach 2:
The system dynamically adjusts validation parameters based on communication context, message importance, and detected threat levels. It changes validation intensity and types of checks performed based on specific conditions, avoiding unnecessary complexity in low-risk scenarios
3Measurement precision
If the system performs real-time validation of all messages, then detection precision of malware is improved, but processing time and system performance decrease
Solution Approach 1:
The system performs partial validation on all messages and excessive (full) validation only on suspicious or critical messages. It applies lightweight attribute checking to every message while reserving comprehensive validation for messages that trigger security concerns, optimizing the balance between detection precision and processing time
Data Source
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AI summary
A system and method for detecting malware includes initiating a mock transaction by sending a mock message to at least one of: an entity internal to a system and an entity external to the system; obtaining a response message related to the mock message; and determining that a malware is modifying messages exchanged between system entities based on at least one of: attributes of the response message and content of the response message.