Socially-Aware Data Storage User Discovery Filtering
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Solution Overview
Problem
Existing social networking websites face challenges in managing user discovery requests across different platforms, leading to authentication issues and unsolicited data access, with no intelligent mechanism to filter responses based on user social profiles.
Innovation Solution
A socially-aware data storage system computes a social score for clients, using this score to determine which users to include in a list returned in response to a user discovery request, allowing for filtered access based on user preferences and relationships, and employing a challenge protocol for additional verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a user discovery request is sent to a socially-aware data storage system, then the system can provide a list of other users based on social scores, but the system complexity increases due to the need to compute and process social scores
Solution Approach 1:
The system pre-computes social scores for users and stores them in the data storage system before discovery requests are made. This preliminary action allows the system to quickly filter and return relevant user lists without performing complex calculations in real-time, thus reducing the complexity burden during actual discovery operations while maintaining privacy protection.
Solution Approach 2:
The social score acts as an intermediary mechanism between user discovery requests and the actual user data. Instead of directly querying all users or relying on traditional authentication methods, the system uses social scores as a filtering layer that mediates the discovery process, protecting privacy while enabling relevant discoveries.
2Ease of operation
If traditional authentication methods are used for cross-website data access, then data access requests can be processed, but authentication issues and security risks increase
Solution Approach 1:
The system changes the authentication parameter from traditional username/password verification to social score-based filtering. Instead of relying on conventional authentication mechanisms that create security risks across different websites, the system uses social scores as a new parameter that automatically determines access eligibility, simplifying operations while improving reliability.
3Loss of information
If all users are included in discovery responses, then complete user lists are provided, but unwanted data access and privacy violations occur
Solution Approach 1:
The system extracts only the relevant portion of user data by filtering the discovery response based on social scores. Instead of providing complete user lists that include unwanted contacts, the system extracts and returns only those users whose social scores indicate compatibility with the requesting user, thus protecting privacy while maintaining discovery efficiency.
Data Source
AI summary
Information processing techniques for managing user discovery requests in a computing system such as a socially-aware data storage system. In one example, a method comprises the following steps. A user discovery request is sent from a first client to a socially-aware data storage system. The user discovery request comprises a social score computed for the first client. A list of other clients associated with the socially-aware data storage system is received at the first client from the socially-aware data storage system. The list of other clients is based on the social score computed for the first client.