Hardware Data Flow Simulation for Safety-Critical Leak Detection
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Solution Overview
Problem
Current methods for detecting security-relevant data flows in hardware systems are inefficient and difficult to automate, especially in scenarios where access to source code or complete system descriptions is limited, making it challenging to identify and address security vulnerabilities effectively.
Innovation Solution
A method that simulates the hardware system in a simulation environment, allowing for the observation and logging of data flows without modifying the hardware, by dividing the system into components with communication, memory, and processor units, and defining critical data properties to identify security-relevant flows, which can be monitored and evaluated for security vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review and auditing of hardware system architecture and implementation are used to detect security vulnerabilities, then detection thoroughness is improved, but time consumption and difficulty of automation increase significantly
Solution Approach 1:
The patent creates a simulation model that copies the hardware system's architecture, components, and data flows. This virtual replica enables automated analysis of security-relevant data flows without manual intervention, achieving both thorough detection and time efficiency. The simulation model includes communication devices, hardware components, and data flow representations that mirror the actual system.
Solution Approach 2:
The patent replaces manual mechanical review processes with automated simulation and analysis systems. Instead of human experts manually auditing hardware architecture, the system uses automated simulation environments to detect security vulnerabilities, significantly reducing time consumption while maintaining or improving detection thoroughness.
2Extent of automation
If static code analysis or model inspection methods are used to detect security vulnerabilities, then automation is improved, but detection effectiveness deteriorates due to inability to find leaks in processing chains and hardware vulnerabilities
Solution Approach 1:
The patent creates a simulation model that copies the hardware system's architecture, components, and data flows. This virtual replica enables automated analysis of security-relevant data flows without manual intervention, achieving both thorough detection and time efficiency. The simulation model includes communication devices, hardware components, and data flow representations that mirror the actual system.
Solution Approach 2:
The patent changes the analysis approach from static code inspection to dynamic simulation with defined parameters for critical data identification. By parameterizing the simulation to track specific data flows marked as critical, the system achieves both automation and effectiveness in detecting security vulnerabilities that static methods miss.
3Measurement precision
If the hardware system is analyzed in its original form to detect security-relevant data flows, then detection accuracy is improved, but ease of operation and automation capability worsen due to system complexity and lack of access to source code
Solution Approach 1:
The patent creates a simulation model that copies the hardware system's architecture, components, and data flows. This virtual replica enables automated analysis of security-relevant data flows without manual intervention, achieving both thorough detection and time efficiency. The simulation model includes communication devices, hardware components, and data flow representations that mirror the actual system.
Solution Approach 2:
The patent introduces a simulation environment as an intermediary between the analyst and the actual hardware system. This intermediary layer provides ease of operation by allowing analysis through simulation rather than direct hardware interaction, while maintaining detection accuracy through faithful replication of system behavior and data flows.
Data Source
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AI summary
A method for detecting safety-relevant data streams which occur in a hardware system (1) during the execution of at least one data processing task (2). The method has the following steps: defining critical data (6), which may be stored in at least one storage unit (3) of the hardware system. Mapping the hardware system (1) onto a simulation model (5) capable of running in a simulation environment (4). Executing the data processing task (2) as a simulation with the simulation model (5) in the simulation environment (4). Monitoring the creation, transmission and deletion of the critical data (6) and of instances (6', 6'') of the critical data (6) in the simulation model (5) during the execution of the data processing task (2). Identifying and logging the safety-relevant data streams.