Anticipated Data Integrity Check Value for Message Validation
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Solution Overview
Problem
Existing data integrity check systems are inefficient in validating message content that changes during transmission to and from a System Under Test (SUT), as they rely on checksums or hash values computed before changes occur, leading to false positives for expected modifications.
Innovation Solution
The implementation of an Anticipated Data Integrity Check Value (ADICV) is generated based on expected modifications to message data, allowing for validation of message data integrity by comparing it with a computed value after processing by the SUT, using a validation map to determine which message portions to inspect.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data integrity check values are computed before message processing, then data integrity validation can be performed, but false positives occur for expected modifications
Solution Approach 1:
The patent applies preliminary action by computing the anticipated data integrity check value (ADICV) in advance, but specifically calculating it based on expected modifications that will occur during processing. The ADICV is computed using at least one value based on at least one expected modification to message data, so when the message is processed and returns, the validation compares against this pre-computed anticipated value rather than the original pre-processing value, eliminating false positives for expected changes.
2Reliability
If data integrity checks are performed on all message data, then complete validation is achieved, but processing efficiency decreases
Solution Approach 1:
The patent extracts and validates only the critical portions of message data that are subject to unexpected modifications. By using the ADICV computed based on expected modifications, the system focuses validation efforts on the specific data elements that matter, rather than performing exhaustive checks on all message content, thereby improving processing efficiency while maintaining validation effectiveness.
Data Source
AI summary
Methods, systems, and computer readable media for providing an anticipated data integrity check are disclosed. According to one method, the method includes generating a test message including an anticipated data integrity check value (ADICV), wherein the ADICV is computed using at least one value based on at least one expected modification to message data in the test message by at least one system under test (SUT), and sending the test message to the at least one SUT.