Keyword Density Calculation for Confidential Data Detection

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Solution Overview

Problem

Existing data loss prevention systems often produce false positives when detecting confidential data in text, due to missing keywords, varying keyword distances, and incorrect identification of data types, leading to unnecessary alarms.

Innovation Solution

A method and system that calculates the density of keywords in text data by determining the ratio of keyword characters or words to total characters or words, using weighting factors and threshold values to accurately identify confidential data, thereby reducing false alarms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If keyword detection method is used to identify confidential data, then detection capability is provided, but false positives increase due to missing keywords, varying distances, and incorrect data type identification

Engineering Contradiction:

Improvedetection accuracyVSAvoidkeyword matching precision

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The patent changes the detection parameter from simple keyword presence to keyword density ratio. Instead of checking if keywords exist in text, the system calculates the ratio of keyword characters to total text characters, and compares this density against threshold values. This parameter transformation resolves the contradiction by providing both detection capability and reduced false positives through quantitative measurement rather than qualitative matching.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If multiple keywords are searched to detect confidential data, then detection coverage is improved, but false alarms increase due to incorrect identification of data types

Engineering Contradiction:

Improvedetection reliabilityVSAvoidfalse positive rate

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent applies partial action by using only the necessary portion of keyword information (the density ratio) rather than requiring complete keyword patterns. By calculating the proportion of keyword characters relative to total text characters, the system achieves reliable detection without needing to verify complete data type structures, thus reducing false alarms while maintaining detection coverage.

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If keyword density calculation is performed to reduce false positives, then detection accuracy improves, but computational complexity increases

Engineering Contradiction:

Improvedetection precisionVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent extracts only the essential information needed for detection - the character count of keywords and total text - and calculates the density ratio from these extracted values. This extraction approach simplifies the system by focusing only on the critical parameter (keyword density) rather than analyzing complete keyword patterns or data type structures, thereby reducing computational complexity while maintaining high detection precision.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS11042659B2System and method of determining text containing confidential data

Publication Date: 2021.06.22 AO KASPERSKY LAB

AI summary

Disclosed are systems and methods preventing data loss of confidential data in a computer system. The described technique includes searching text data for one or more keywords, and then calculating a density of keywords in the text data based on the one or more keywords that match the text data. The technique classifies the text data as containing confidential data based on whether the density of keywords exceeds a threshold value. If so, the described systems may block the use of the text data containing confidential data in a variety of ways.