Secret Pattern PII Identification via Predictive Modeling
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Solution Overview
Problem
Conventional techniques fail to provide a robust data tracking system to identify and monitor Personally Identifiable Information (PII) within user data, especially in large-scale enterprises with complex data flows and growing privacy concerns.
Innovation Solution
A method and system that utilize a predictive model based on a classifier algorithm to identify PII, generate a secret pattern as an identifiable label, and add it to personal identifiers, enabling real-time tracking and storage of PII across data sources and destinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional techniques are used for data management, then data flow tracking becomes increasingly difficult as systems grow, but implementing robust PII identification and tracking systems increases device complexity and processing requirements
Solution Approach 1:
The patent applies preliminary action by embedding secret patterns into PII data during the data collection and processing phases, before the data reaches its final destination. This proactive approach ensures that PII is already marked and trackable throughout its lifecycle, eliminating the need for complex retroactive tracking systems and reducing overall system complexity while maintaining high reliability for privacy protection
2Productivity
If PII is not removed or only partially removed from user data, then data sharing is simplified, but privacy and data protection of users deteriorates
Solution Approach 1:
The patent introduces secret patterns as an intermediary mechanism that enables data sharing while protecting privacy. These patterns act as a mediator between the need for data utility (sharing) and the need for privacy protection, allowing organizations to share PII data with third parties while maintaining the ability to identify and control the flow of personally identifiable information through the embedded patterns
3Measurement precision
If real-time PII identification is implemented during data transmission, then data tracking accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-processing and embedding secret patterns into PII data during initial data collection and storage phases. This ensures that when data is transmitted and needs to be tracked in real-time, the identification process is significantly accelerated because the secret patterns are already in place, reducing computational overhead during transmission while maintaining high identification accuracy
Data Source
AI summary
This disclosure relates to method and system for identifying Personally Identifiable Information (PII) through secret patterns. The method includes receiving user data from at least one data source through a plurality of communication channels. The user data includes PII and non-PII. The user data is associated with a user. The PII includes a plurality of personal identifiers. The method further includes identifying the PII in user data through a predictive model. The method further includes generating a secret pattern based on the PII identified through the predictive model. The secret pattern is an identifiable label. The method further includes adding the secret pattern to each of the plurality of personal identifiers in PII. The method further includes identifying each of the plurality of personal identifiers through the secret pattern in real-time, when user data is transmitted from the at least one data source to at least one data destination.