Misuseability Weight M-Score for Data Leakage Detection
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Solution Overview
Problem
Current methods for detecting data leakage and misuse in databases do not effectively consider the sensitivity level of the data, which is crucial for estimating potential damage, and existing privacy-preserving data publishing measures are not sufficient for all scenarios, especially when users have full access to the data.
Innovation Solution
A system that calculates a Misuseability Weight, or M-score, for all queries made by a user within a time frame, considering the sensitivity level of the data, to determine the potential damage and implement dynamic misuseability-based access control, regulating user access to sensitive data in relational databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data access control is tightened to prevent data leakage, then security is improved, but operational efficiency and user productivity deteriorate
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting access control parameters based on the sensitivity level of data. Instead of a static access control model, the system modifies permission parameters according to the M-score (misuseability weight) of queried data, allowing fine-grained control that adapts to the specific sensitivity context of each data access request.
Solution Approach 2:
The patent implements dynamics by making access control policies dynamic rather than static. The system continuously evaluates the sensitivity level of data being accessed and adjusts user permissions in real-time based on the M-score calculation, enabling the access control mechanism to adapt to changing data sensitivity contexts while maintaining both security and operational efficiency.
2Difficulty of detecting and measuring
If existing detection methods are used without considering data sensitivity, then detection coverage is improved, but detection accuracy and effectiveness deteriorate
Solution Approach 1:
The patent applies local quality by tailoring detection parameters to the specific characteristics of each data element. Instead of uniform detection across all data, the system assigns different detection thresholds and sensitivity levels based on the local quality (sensitivity level) of individual data records, improving detection accuracy for high-sensitivity data while maintaining coverage for lower-sensitivity data.
Solution Approach 2:
The patent uses parameter changes to adjust detection sensitivity dynamically. The M-score calculation modifies detection parameters based on the sensitivity level of the data being accessed, allowing the detection system to adapt its thresholds and criteria to match the specific risk profile of each data element, thereby improving overall detection accuracy.
3Reliability
If access control is made more restrictive to protect sensitive data, then data protection is improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent applies universality by designing a multi-functional access control system that handles multiple objectives simultaneously. The M-score-based access control mechanism serves both security protection and operational efficiency goals within a unified framework, eliminating the need for separate complex systems for each objective and reducing overall system complexity despite enhanced protection capabilities.
Data Source
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AI summary
A computerized method for detecting data leakage and data misuse in a computer system belonging to an organization. The method comprising the steps of determining a raw record score; determining a record distinguishing factor; determining a final record score using the distinguishing factor and the raw record score; and combining the final record score with a quantity factor in order to determine the misuseability weight.