Dynamic Data Masking for Mobile Privacy
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Solution Overview
Problem
Users accessing sensitive data on mobile devices in public spaces face privacy breaches due to exposure of confidential information, as existing solutions do not effectively mask data based on location and network characteristics.
Innovation Solution
A computer-implemented method and system that dynamically masks data on mobile devices by detecting location and network characteristics, using a prediction algorithm to determine if data masking is necessary based on historical user patterns, and applying masking rules to protect sensitive information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is displayed unmasked on mobile device, then user can access and view sensitive information, but privacy is exposed to others in public spaces
Solution Approach 1:
The patent implements dynamic data masking that automatically adjusts between masked and unmasked states based on detected environmental conditions. The system transitions from a static masking approach to a dynamic one that responds to location, time, and network characteristics, allowing data to be masked in public spaces and unmasked in private environments, thus resolving the contradiction between accessibility and privacy protection
Solution Approach 2:
The system changes the masking parameter state based on detected parameters such as geographic location, time of day, and network type. By monitoring these parameter changes and adjusting the masking state accordingly, the system enables full data visibility when safe (private locations) and protects privacy when needed (public locations), simultaneously满足ing accessibility and security requirements
2Object-affected harmful factors
If automatic masking is applied based on location and network characteristics, then privacy protection is enhanced, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically detecting environmental conditions and making independent decisions about masking without requiring user intervention. The device uses its own sensors and processors to monitor location, time, and network characteristics, then autonomously applies or removes masking, reducing the need for complex user-facing controls while maintaining strong privacy protection
Solution Approach 2:
The masking system is designed as a universal solution that handles multiple privacy protection scenarios through a single integrated framework. By combining location detection, time analysis, network characteristic evaluation, and automated masking control into one unified system, the patent reduces overall complexity compared to having separate solutions for each privacy concern
3Object-affected harmful factors
If data masking is applied in all environments, then privacy is protected, but user convenience and data accessibility are reduced
Solution Approach 1:
The system applies different masking qualities to different locations and environments. Instead of uniform masking across all contexts, the patent implements location-specific masking behavior: full masking in public spaces, partial or no masking in private environments. This localized approach to quality control allows privacy protection where needed while maintaining data accessibility where safe
Data Source
AI summary
A computer-implemented method is provided for automatically masking data for display in a mobile computing device. The computer-implemented method includes receiving a request to display data on the mobile computing device and detecting a physical location of the mobile computing device, a time corresponding to the request, and at least one network characteristic of a wireless network on which the mobile computing device is making the request. The method also includes automatically determining whether to mask the data for display in the mobile computing device based on the physical location, the time, and the at least one network characteristic. The method further includes responsive to determining to mask the data, applying one or more masking rules to the data.