Sensitive-Attribute Masking for Privacy-Preserving Service Operations
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Solution Overview
Problem
Existing systems struggle to balance data privacy and service operations, as they lack the ability to prevent malicious or accidental data exposure by authorized personnel, leading to potential data breaches and impacting performance metrics.
Innovation Solution
A system and method that assesses user requests for sensitive attributes, assigns vulnerability ratings, estimates disclosure proportions, and performs masking operations to minimize data exposure while ensuring privacy, using a generalization tree for non-numerical attributes and computing sensitivity scores to allocate requests to appropriate agents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is totally anonymized or hidden to protect privacy, then data privacy is improved, but service operations performance deteriorates
Solution Approach 1:
The patent applies local quality by differentiating the level of data disclosure based on the sensitivity and vulnerability rating of individual attributes. Instead of uniform anonymization, the system masks only the necessary portions of data (e.g., masking middle digits of phone numbers or partial addresses) while preserving essential information needed for service resolution, thus achieving both privacy protection and operational effectiveness.
Solution Approach 2:
The system dynamically adjusts data disclosure parameters based on vulnerability ratings and privacy settings. The masking operation modifies data parameters selectively - changing the visibility of specific attributes based on their risk level, thereby optimizing the balance between privacy protection and service performance requirements.
2Object-affected harmful factors
If role-based access control is implemented to limit data access, then data security is improved, but the ability to detect malicious authorized personnel deteriorates
Solution Approach 1:
The system implements feedback mechanisms that monitor agent behavior and data access patterns in real-time. The feedback alert system detects anomalies such as excessive data requests, unusual access patterns, or attempts to access masked data, enabling the system to identify and respond to malicious activities by authorized personnel while maintaining security controls.
Solution Approach 2:
The patent introduces an intermediary monitoring layer between data access and service operations. This intermediary system tracks and analyzes agent interactions with data, providing detection capabilities for malicious behavior while preserving the role-based access control structure. The intermediary acts as a detector that observes without interfering with normal operational flows.
3Reliability
If data disclosure is minimized to prevent insider threats, then data privacy is improved, but the quantity of information available for service resolution deteriorates
Solution Approach 1:
The system applies partial action by masking only the necessary portions of data rather than complete anonymization. The masking operation reveals sufficient information for service resolution (e.g., showing first and last digits of phone numbers, or partial addresses) while hiding sensitive portions, thus preventing insider threats while maintaining operational effectiveness.
Solution Approach 2:
The patent segments data disclosure based on vulnerability ratings of individual attributes. Each attribute is evaluated independently, and masking is applied selectively to specific segments of data (e.g., masking middle digits of phone numbers, masking specific portions of addresses) while leaving other segments visible, thereby optimizing the balance between privacy and information availability.
Data Source
AI summary
This disclosure relates generally to method and system for providing data privacy in service operations. Identifying risk arising from processing of user request in service operations is time consuming and monitoring insider threats is a difficult task. The method includes receiving a user request for a service comprising a plurality of sensitive attributes and further a vulnerability rating is assigned to each sensitive attribute. To mitigate the risk, the method estimates a disclosure proportion for the plurality of sensitive attributes and a masking operation is performed. Further, a sensitivity score is computed to allocate the user request to an agent associated with an agent registry with enabled data privacy and minimal data exposure. The agent is monitored by computing an agent mis-usability score to assess an insider threat risk. Additionally, a feedback alert is notified to autotune the plurality of privacy settings.