Clickstream Data Cleansing for Private Information Removal
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Solution Overview
Problem
Existing systems fail to effectively identify and remove private user information from clickstream data, which includes sensitive personal details that should be protected.
Innovation Solution
A method and system that utilizes software programs to detect and remove private user information by applying proximity thresholds and identification rules, using client-server architecture to identify and cleanse clickstream data before transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If clickstream data is collected for research analysis, then research value is improved, but private user information exposure increases
Solution Approach 1:
The patent extracts and removes private user information from clickstream data while retaining the remaining data for research analysis. The system identifies patterns indicating private information (such as credit card numbers, social security numbers, email addresses) and extracts only those specific elements for removal, leaving the rest of the clickstream data intact for research purposes.
Solution Approach 2:
The patent performs preliminary detection and removal of private information before the data is transmitted or stored for research analysis. By proactively identifying and redacting sensitive elements in advance, the system ensures that private information never enters the research dataset, thereby eliminating the harmful effect while preserving research value.
2Measurement precision
If comprehensive data collection is performed, then analysis accuracy is improved, but privacy protection becomes more difficult
Solution Approach 1:
The patent implements self-service privacy protection where the system automatically detects, identifies, and removes private information without requiring manual intervention. The automated detection mechanisms scan data streams, recognize patterns indicating sensitive information, and redact them automatically, making privacy protection straightforward despite comprehensive data collection.
Solution Approach 2:
The patent changes the state of private information from visible to redacted by modifying data parameters. When private information is detected, the system transforms it into a redacted form (such as replacing with asterisks or removing entirely), thereby maintaining data structure and analysis capability while eliminating privacy risks.
3Measurement precision
If manual review of clickstream data is performed, then privacy detection accuracy is improved, but processing efficiency decreases
Solution Approach 1:
The patent replaces manual mechanical review processes with automated computational detection systems. The system uses algorithmic patterns and rules to automatically identify private information types (credit card numbers, social security numbers, email addresses, etc.), substituting human reviewers with automated software that achieves comparable or superior detection accuracy while dramatically increasing processing efficiency.
Solution Approach 2:
The patent introduces an intermediary automated detection layer between raw clickstream data and final analysis. This intermediary system scans data streams, identifies private information using pattern recognition, and redacts sensitive elements before data reaches researchers, thereby maintaining high detection accuracy while enabling rapid automated processing of large datasets.
Data Source
AI summary
A method, a computer program, or a computerized system for a first software program to remove private user information from a collection of data items communicated by a second software program to a third software program. The first software program may receive the data collection from the second software program, detect in the data collection a first indicator associated with the particular private user information, detect in the data collection the private user information within a proximity threshold associated with the first indicator, remove the private user information from the data collection to form cleaned data collection, and provide the cleaned data collection to the second software program.