Keyword Proximity Matching for Sensitive Data Detection
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Solution Overview
Problem
The increasing complexity of data protection due to the explosion of messaging systems and USB storage devices poses challenges for enterprises in preventing data leakage, leading to loss and theft of sensitive information.
Innovation Solution
An apparatus and method for keyword matching that includes a processor and data storage, utilizing a keyword searcher and object generator to implement range-dependent and proximity matching techniques to detect sensitive information in documents, reducing false positives and enabling regulatory compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional keyword matching is used to detect sensitive information, then the detection process is simple and fast, but false positives increase and detection precision decreases
Solution Approach 1:
The patent segments the keyword matching process into multiple stages: generating candidate keywords from the document, filtering candidates against the keyword list, and verifying matches using proximity rules. This segmentation allows the system to maintain high detection precision while managing complexity through structured processing steps.
Solution Approach 2:
The patent introduces dynamic proximity parameters that allow the matching criteria to adapt based on the document context. The proximity threshold and weighting factors can be adjusted dynamically to balance between detecting true sensitive information and avoiding false positives, thereby improving detection precision without requiring overly complex static rules.
2Reliability
If keyword proximity matching with range-dependent functions is implemented, then false positives are reduced, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing the document to extract potential keywords and their positions before applying the proximity matching logic. This preliminary keyword extraction creates a filtered set of candidates, reducing the computational burden of subsequent proximity calculations and minimizing processing time while maintaining reliable detection.
Solution Approach 2:
The patent replaces traditional mechanical keyword matching with a more sophisticated system that uses proximity-based scoring and weighting mechanisms. This substitution improves reliability by considering contextual relationships between keywords, while the use of efficient data structures and algorithms mitigates the increase in processing time.
3Measurement precision
If advanced proximity matching techniques are used, then detection accuracy improves, but the complexity of implementation and operation increases
Solution Approach 1:
The patent introduces an intermediary layer that translates complex proximity matching logic into simplified operational interfaces. This intermediary handles the complexity of range-dependent functions and proximity calculations internally, while presenting a user-friendly interface that maintains high matching accuracy without requiring users to understand the underlying complexity.
Data Source
AI summary
One embodiment relates to an apparatus configured to match a list of keywords against a target document. The apparatus includes data storage configured to store computer-readable instruction code and data, and a processor configured to access the data storage and to execute said computer-readable instruction code. The apparatus further includes a keyword searcher and a keyword object generator. The keyword searcher is configured to receive the list of keywords and a textual string corresponding to the target document file, and search the textual string for instances of the keywords so as to generate a sequence of keyword instances. The keyword object generator implemented using the instruction code and configured to receive the sequence of keyword instances, and generate a keyword object, wherein the keyword object includes a range-dependent match function. Other embodiments and features are also disclosed.