Vehicle Security Log Analysis for Multi-Attack Scenario Detection
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Solution Overview
Problem
Current vehicle security operation centers struggle to accurately analyze diversified cyberattacks on connected vehicles, as they primarily focus on individual attacks rather than the relationships between multiple attack patterns occurring within a predetermined time period.
Innovation Solution
A vehicle security analysis apparatus and method that acquires and analyzes sensor log data to identify individual attack patterns and then matches these patterns with predefined scenarios, generating analysis information to output comprehensive attack scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vehicle security operation centers analyze only individual attacks separately, then the analysis process is simple and straightforward, but the ability to identify diversified attack scenarios and relationships between multiple attacks is insufficient
Solution Approach 1:
The patent segments the attack analysis process into distinct modules: an individual attack pattern identification unit that analyzes single attacks, and an attack scenario identification unit that analyzes relationships between multiple attacks. This segmentation allows the system to handle both simple individual attacks and complex diversified scenarios without overwhelming complexity, resolving the contradiction between adaptability and device complexity.
Solution Approach 2:
The patent transitions from one-dimensional individual attack analysis to two-dimensional attack scenario analysis by adding a temporal dimension (analyzing attacks within predetermined time periods) and a relational dimension (identifying relationships between multiple attack patterns). This dimensional expansion enables the system to identify diversified attack scenarios while maintaining structured analysis through the modular architecture.
2Measurement precision
If the system analyzes relationships between multiple attack patterns within predetermined time periods, then the identification accuracy of attack scenarios improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary action by first identifying individual attack patterns and storing them in a database before analyzing attack scenarios. The individual attack pattern identification unit pre-processes and categorizes attacks, creating a foundation that accelerates subsequent scenario analysis. This preliminary structuring reduces the computational burden during scenario identification, balancing accuracy with processing time.
Solution Approach 2:
The patent introduces an intermediary mechanism in the form of a predetermined time period window and relationship determination rules that mediate between raw attack data and final scenario identification. This intermediary layer filters and structures the data, enabling accurate scenario identification without requiring exhaustive analysis of all possible attack combinations, thus reducing processing time while maintaining precision.
3Reliability
If the system focuses on individual attack analysis, then the analysis method is simple and fast, but it cannot accurately analyze diversified cyberattacks that involve multiple attack patterns
Solution Approach 1:
The patent divides the analysis system into segmented functional units: an individual attack pattern identification unit for simple, fast analysis of single attacks, and an attack scenario identification unit for accurate analysis of diversified attacks involving multiple patterns. This segmentation allows the system to maintain simplicity where applicable while adding complexity only where necessary for accurate diversified attack analysis, resolving the contradiction between reliability and device complexity.
Solution Approach 2:
The patent creates a universal analysis framework that can handle both individual attacks and diversified attack scenarios through a single integrated system. The attack scenario identification unit serves multiple functions by analyzing relationships between different attack patterns, temporal sequences, and contextual information, enabling accurate analysis of diverse cyber threats without requiring separate specialized systems for each attack type.
Data Source
AI summary
The vehicle security analysis apparatus generates, based on sensor log data items generated in in-vehicle devices, a combination of sensor log data items by associating a plurality of sensor log data items having a possibility of constituting the same individual attack, and identifies an individual attack pattern by comparing this combination of the sensor log data items with individual attack knowledge information. Next, a combination of a plurality of individual attack patterns that have occurred within a predetermined time period is compared with attack scenario knowledge information to identify an attack scenario. Then, the analysis result including the identified individual attack pattern and attack scenario is output.