Heterogeneous Indicia Engine for Cloud Transaction Integrity
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Solution Overview
Problem
Current systems lack effective methods to detect and prevent computational errors caused by hardware, firmware, or software faults, as well as malware infections in transaction processing systems, which can lead to data integrity issues and system failures.
Innovation Solution
The implementation of a Heterogeneous Indicia Engine (HIE) system, where multiple computing subsystems of different manufacture process transactions and compare indicia to verify the validity of results, allowing only matching results to be committed and identifying mismatched subsystems for further diagnostics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a Logical Synchronization Unit is used to compare outputs of redundant subsystems, then system reliability is improved, but device complexity increases
Solution Approach 1:
The patent removes the Logical Synchronization Unit from the system architecture. Instead of using a centralized LSU to compare outputs of redundant subsystems, the system uses distributed comparison where each subsystem independently verifies its output against a trusted reference, eliminating the complex centralized comparison mechanism while maintaining reliability
Solution Approach 2:
The patent introduces a Trusted Reference as an intermediary that provides the ground truth for verification. Rather than having subsystems compare each other through a complex synchronization unit, each subsystem compares its output against this trusted reference, simplifying the overall system architecture while ensuring reliability
2Reliability
If multiple subsystems process transactions and compare indicia to verify validity, then data integrity is improved, but processing time increases
Solution Approach 1:
The patent performs verification actions before transaction commitment. Each subsystem calculates indicia representing its transaction results and compares them against the Trusted Reference in advance. Only transactions with matching indicia are committed, ensuring data integrity while allowing parallel processing of independent transactions to minimize time loss
Solution Approach 2:
The patent uses indicia as compressed representations or copies of transaction results. Instead of comparing full transaction outputs, the system calculates and compares condensed indicia that capture the essential verification information, reducing the time required for comparison while maintaining data integrity verification
3Reliability
If subsystems of different manufacture are used to process transactions, then detection of malicious or faulty operations is improved, but device complexity increases
Solution Approach 1:
The patent deliberately uses subsystems of different manufacture (asymmetric configuration) to process transactions. This asymmetry ensures that different subsystems may have different vulnerabilities or faults, improving the ability to detect malicious or faulty operations. The Trusted Reference provides a consistent baseline against which all asymmetric subsystems are compared
Solution Approach 2:
The patent applies local verification where each subsystem independently compares its output against the Trusted Reference. This localized comparison approach allows different subsystems to operate with different characteristics while maintaining overall system reliability, avoiding the need for complex centralized coordination
Data Source
AI summary
A method is provided to verify the computational results of a transaction processing system utilizing cloud resources. A transaction is allowed to modify an application's state only if the validity of the result of the processing of the transaction is verified across the majority of the participating child nodes in the cloud. Otherwise, the transaction is aborted.