PI Data Detection Using Hash Comparison Across Computing Environments
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Solution Overview
Problem
Existing methods for detecting personally identifiable data (PI) in computing environments are tedious and time-consuming, requiring manual scouring across different environments to identify unauthorized breaches, necessitating an automated detection solution.
Innovation Solution
A computer-automated method using a modifiable hash algorithm and PI detector service function to mask PI data, compare electronic data fields, and generate a confidence level report, with features like data conversion, normalization, and encryption, supported across various programming languages and databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection methods are used to identify PI data in computing environments, then detection accuracy can be maintained, but the process becomes tedious and time-consuming
Solution Approach 1:
The system enables self-service automated detection of PI data through hash algorithms and comparison services that automatically scan computing environments without requiring manual human intervention, thereby reducing detection time while maintaining accuracy through systematic automated processes
Solution Approach 2:
The patent replaces manual mechanical scanning processes with automated computational systems including hash algorithms and detector services that systematically process and compare data fields, substituting human effort with automated mechanical-computational processes to reduce time loss
2Productivity
If automated detection systems are implemented to scan computing environments, then detection efficiency is improved, but the system complexity increases
Solution Approach 1:
The detection system is segmented into distinct functional components: a hash algorithm component that processes data, a detector service function that performs comparisons, and a result generation component. This segmentation allows each component to be independently optimized and managed, improving overall detection efficiency while controlling complexity through modular design
Solution Approach 2:
The hash algorithm serves as an intermediary that transforms original data into a comparable format before the detector service function performs the actual comparison. This intermediary step simplifies the detection process by converting complex data matching into a more manageable hash comparison operation
3Extent of automation
If data is transmitted between computing environments for detection, then automated detection capability is achieved, but data security risks increase
Solution Approach 1:
Instead of transmitting sensitive PI data between computing environments, the system creates and processes hash copies of the data. The hash algorithm generates a transformed representation that can be safely transmitted and compared without exposing the original sensitive information, thus achieving automated detection while mitigating data security risks
Data Source
AI summary
A method and system of computer-automated detection of personally identifiable (PI) data in electronic data are provided. The method includes: receiving the electronic data including the PI data and transmitting the electronic data to a modifiable hash algorithm in a first computing environment. The method further includes generating, by the modifiable hash algorithm, hashed electronic data via masking the PI data; comparing, by a PI detector service function algorithm in a second computing environment, first electronic data fields of the received electronic data including the PI data with second electronic data fields of the hashed electronic data including the masked PI data in order to detect a match indicating a presence of unmasked PI data between the first and second electronic data fields; generating, by the PI detector service function algorithm, a result with a confidence level based on the comparison; and outputting the result with the confidence level.