Two-Tier Data Modification Detection for Schema Mismatch
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Solution Overview
Problem
Conventional data modification detection techniques in networks are prone to false positives, inefficient, and require manual intervention, leading to network congestion and reduced operational efficiency due to inconsistent data representation and format changes.
Innovation Solution
A two-tiered assessment approach is employed, first checking for schema consistency and then comparing descriptive elements, to accurately detect data modifications, reducing false positives and optimizing computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional data modification detection techniques are used, then data changes can be detected, but false positives increase and operational efficiency decreases due to manual intervention requirements
Solution Approach 1:
The patent segments the data comparison process into two distinct levels: schema-level comparison and data element-level comparison. This segmentation allows the system to first filter incompatible data formats at the schema level, preventing false positives, and then perform detailed comparison only on compatible data, improving both accuracy and efficiency
Solution Approach 2:
The patent performs preliminary schema consistency checking before conducting detailed data element comparison. This preliminary action filters out incompatible data representations early in the process, preventing false positives and reducing the computational burden of subsequent detailed comparisons, thereby improving operational efficiency
2Measurement precision
If manual intervention is implemented for data modification detection, then detection precision can be maintained, but network congestion increases and processing time extends
Solution Approach 1:
The patent implements an automated two-level assessment system that performs schema consistency checking and data element comparison without manual intervention. The system self-identifies modifications by comparing received descriptive information against stored elementary information, maintaining detection precision while eliminating the time loss associated with manual processing
Solution Approach 2:
The system performs preliminary automated schema validation before detailed comparison, quickly filtering out incompatible data representations. This preliminary automated action maintains detection precision by ensuring only valid data undergoes detailed comparison, while significantly reducing processing time compared to fully manual intervention
3Reliability
If comprehensive data comparison is performed without schema filtering, then all modifications are detected, but computational resources are wasted on incompatible data
Solution Approach 1:
The patent divides the comparison process into schema-level and data-element level segments. The schema-level comparison quickly identifies incompatible data representations, allowing the system to skip detailed comparison for those cases. This segmentation ensures detection completeness for compatible data while avoiding waste of computational resources on incompatible data
Solution Approach 2:
The patent applies partial comparison action by performing detailed data element comparison only on data that passes schema consistency checks. Instead of performing excessive comprehensive comparison on all data including incompatible representations, the system selectively applies detailed comparison only where necessary, optimizing computational resource efficiency while maintaining detection completeness
Data Source
AI summary
Techniques for data modification detection are disclosed. Descriptive information, including a resource identifier and a set of descriptive elements having a schema of representation, is received from a resource. Further, elementary information, including at least one of elementary resource identifier and set of elementary descriptors having an elementary schema of representation, corresponding to the resource is retrieved from a resource inventory database. A preliminary assessment is performed to assess similarity between the schema of representation and the elementary schema of representation. If the schemas are ascertained to be similar, a subsequent check is then performed to deduce a similarity between the set of descriptive elements and the set of elementary descriptors. Based on the subsequent assessment, an information-variance signal is generated to trigger rendering of an indication to indicate a probable modification of the set of descriptive elements in comparison with the set of elementary descriptors.