Root-of-Trust Cross-Validation for Tamper Detection
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Solution Overview
Problem
Existing computing systems are vulnerable to attacks on their Hardware Root of Trust (HWRoT), which can lead to compromised subsystems performing unauthorized activities, and there is no effective mechanism to detect such attacks on the HWRoT itself.
Innovation Solution
Implementing multiple subsystems with respective RoTs that perform inter-mutual validation, where each RoT validates the information of other subsystems, allowing cross-checking and detection of tampering, and a ballot engine evaluates the validation results to determine trustworthiness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single HWRoT is used to validate subsystems, then the system is simpler to implement, but the system becomes vulnerable to attacks on the HWRoT itself with no detection mechanism
Solution Approach 1:
The patent divides the trust validation function into multiple independent RoTs (first RoT, second RoT, third RoT) distributed across different subsystems. Each RoT validates other subsystems but not its own, creating a segmented validation architecture that eliminates the vulnerability of a single centralized HWRoT while maintaining overall system simplicity through modular design.
2Measurement precision
If multiple RoTs perform inter-mutual validation, then the detection of tampering is improved, but the validation process becomes more complex
Solution Approach 1:
The patent introduces a ballot engine as an intermediary that collects validation results from multiple RoTs, evaluates them according to predefined policies, and determines overall system trustworthiness. This mediator simplifies the complex inter-mutual validation process by centralizing the evaluation logic, thereby improving tamper detection accuracy without proportionally increasing process complexity.
Solution Approach 2:
The system implements feedback loops where each RoT validates other subsystems and reports results to the ballot engine, which then evaluates these results and can trigger remediation actions. This feedback mechanism enables precise tamper detection through cross-validation while managing complexity through structured information flow and automated decision-making.
3Reliability
If inter-mutual validation is implemented among multiple RoTs, then the reliability of trust validation is enhanced, but the system complexity increases
Solution Approach 1:
The trust validation function is segmented across multiple independent RoTs distributed in different subsystems, with each RoT responsible for validating specific other subsystems. This segmentation enhances reliability through distributed validation while managing architectural complexity by assigning clear, non-overlapping validation responsibilities to each RoT.
Solution Approach 2:
The ballot engine serves as a universal component that handles validation result collection, evaluation, and trust determination for all subsystems. This multi-functional intermediary simplifies the overall system architecture by providing a centralized evaluation layer that works across all RoTs and subsystems, reducing the need for complex point-to-point validation logic.
Data Source
AI summary
In some examples, a system includes a plurality of subsystems associated with respective root of trusts (RoTs). The RoTs include a first RoT to validate information of a first subsystem of the plurality of subsystems, and a second RoT to validate information of a second subsystem of the plurality of subsystems. The RoTs further perform inter-mutual validation that includes the first RoT validating the information of the second subsystem, based on the first RoT validating the second subsystem, providing, by the first RoT, an indication of successful validation of the second subsystem, and based on the indication, the second RoT validating the information of the first subsystem.