Privacy Profile Generation for Web Session Data Filtering
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Solution Overview
Problem
Current monitoring and replay systems fail to effectively filter sensitive personal information from captured web session data, leading to potential privacy breaches and inefficient processing, as they struggle to adapt to changes in web page names or field names, resulting in incorrect filtering and resource wastage.
Innovation Solution
A privacy processing system that applies privacy rules to captured web session data, generates privacy profiles to identify filtering issues, and uses metrics to detect deviations, allowing for the efficient filtering and encryption of sensitive information, thereby ensuring compliance with privacy regulations and maintaining data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current monitoring and replay systems filter sensitive personal information using fixed privacy rules, then some personal information can be removed, but the system fails to adapt to changes in web page names or field names, resulting in incomplete filtering
Solution Approach 1:
The system performs preliminary actions by capturing and storing metadata about web pages and fields before filtering occurs. This metadata includes information about the structure, names, and characteristics of web elements at the time of capture, enabling the privacy rules to adapt to future changes in web page names or field names while maintaining accurate filtering.
Solution Approach 2:
The system implements feedback mechanisms where captured metadata about web pages and fields is used to refine and update privacy rules. This feedback loop allows the system to learn from actual web page structures and adjust filtering criteria accordingly, improving both accuracy and adaptability to changing web applications.
2Reliability
If the system destroys captured web session data when sensitive personal information is not successfully filtered, then privacy compliance is maintained, but processing efficiency and data availability for analysis are reduced
Solution Approach 1:
By capturing and storing metadata about web pages and fields in advance, the system can perform more effective filtering before data destruction is needed. This preliminary capture of structural information enables better matching with privacy rules, increasing the likelihood of successful filtering and reducing the need to destroy data.
Solution Approach 2:
The system uses the captured web session data itself to generate metadata about its own structure and content. This self-service approach allows the system to automatically understand and adapt to the data it is processing, improving filtering effectiveness without requiring external intervention or data destruction.
3Ease of operation
If privacy rules are triggered based on web page names or field names, then filtering can be applied, but changes in naming conventions cause incorrect triggering or missed filtering
Solution Approach 1:
The system captures and stores metadata about web page names, field names, and their structural characteristics before filtering is applied. This preliminary capture preserves the context and structure of the data at the time of capture, allowing privacy rules to accurately match and filter information even when naming conventions change in the future.
Solution Approach 2:
The system stores multiple parameters about web pages and fields, including names, types, positions, and structural relationships. By maintaining this comprehensive parameter set, the system can adapt to changes in any single parameter while maintaining accurate filtering through the relationship context captured in the metadata.
Data Source
AI summary
A privacy processing system may use privacy rules to filter sensitive personal information from web session data. The privacy processing system may generate privacy profiles or privacy metadata that identifies how often the privacy rules are called, how often the privacy rules successfully complete actions, and the processing time required to execute the privacy rules. The privacy profiles may be used to detect irregularities in the privacy filtering process that may be associated with a variety of privacy filtering and web session problems.