Hybrid Interface for Multi-User Privacy and Memory Efficiency
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Solution Overview
Problem
Traditional data visualization systems in financial and business interfaces fail to provide personalized data to multiple users accessing a common account while maintaining privacy, leading to generic and unsecured information presentation.
Innovation Solution
The system generates a hybrid interface with blended, personalized, and obscured data for multiple users accessing a common device, using dynamic interface modification and privacy circuitry to ensure that each user only sees their respective personalized information, reducing memory burdens and ensuring data privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional static interfaces present generic account data to multiple users on a common device, then all users can view all information, but user data privacy is compromised and personalization is lost
Solution Approach 1:
The interface is segmented into multiple distinct interface instances, each tailored to a specific user. The system divides the common display into separate viewable areas or overlays, where each user sees only their personalized interface portion. This segmentation allows personalized information to be presented while preventing other users from accessing it, thus resolving the contradiction between privacy and information delivery.
Solution Approach 2:
Different regions or layers of the display interface are assigned different quality attributes based on user identity. Each user's personalized data is rendered with specific visibility properties (such as opacity, position, or accessibility) that are local to that user's context. This allows the interface to simultaneously present generic shared information to all users while delivering personalized information selectively to individual users, maintaining both privacy and information completeness.
2Reliability
If separate user interfaces are generated for each user on a common device, then personalized data privacy is maintained, but memory burden increases
Solution Approach 1:
Multiple user interfaces are merged into a single hybrid interface instance that is rendered once on the common display device. Instead of generating and maintaining separate interface instances for each user (which would consume excessive memory), the system combines all user-specific personalization parameters into one unified interface structure. This single hybrid interface dynamically adapts its content and presentation based on the active user's identity, achieving data privacy through selective visibility rather than through interface duplication, thus minimizing memory resource consumption.
3Quantity of substance
If a single generic interface is used for multiple users, then memory resources are conserved, but personalized information cannot be selectively presented
Solution Approach 1:
The interface is designed as a dynamic hybrid structure that can adapt its content, layout, and visibility properties in real-time based on the active user's identity. When a user interacts with the common device, the system dynamically modifies the single interface instance to present personalized information appropriate to that user while maintaining the same underlying interface framework. This dynamic adaptability allows the interface to provide personalized experiences across multiple users without requiring separate static interface instances for each user, thus conserving memory resources while achieving versatility.
4Ease of operation
If personalized interface data is displayed to each user, then user experience is improved, but other users can potentially view each other's private information
Solution Approach 1:
Multiple layers of interface content are nested within a single display structure, with each layer representing a different user's personalized information. The system employs layered rendering where user-specific content is placed in nested layers that are selectively visible or invisible based on the active user's identity. This nesting approach allows personalized information to be prepared and structured for multiple users simultaneously while ensuring that only the appropriate layer is actively displayed to each user, preventing information exposure while maintaining excellent user experience for all users.
Data Source
AI summary
Methods, apparatuses, and computer program products are disclosed for dynamic user interfaces. An example computer-implemented method includes receiving a communication channel request from a user device and establishing a communication channel with the user device. The computer-implemented method also includes receiving an indication that a first user and a second user are accessing the communication channel via the user device and generating a hybrid interface. The hybrid interface includes blended interface data based upon first user parameter data associated with the first user and second user parameter data associated with the second user, first personalized interface data based upon the first user parameter data, and second personalized interface data based upon the second user parameter data. The computer-implemented method may include causing the first personalized interface data and/or the second personalized interface data to be obscured.