Social Network Access Control via Suspicious Object Clustering
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Solution Overview
Problem
Existing technologies fail to effectively limit user access to specific suspicious objects on social networks without restricting access to the entire social network, posing a security risk, especially for children.
Innovation Solution
A system and method that constructs a social graph for a user profile, identifies clusters of users, determines suspicious objects linked to forbidden objects, and uses a blocking module to restrict access to these objects, thereby isolating suspicious content while maintaining access to the social network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If parental control software limits access to the entire social network, then security against suspicious objects is improved, but user accessibility to the social network deteriorates
Solution Approach 1:
The patent segments the social network into individual objects (profiles, groups, content elements) and enables selective blocking of suspicious objects while maintaining access to the rest of the network. The system identifies suspicious objects through clustering algorithms and allows users to block specific objects rather than the entire network, thus resolving the contradiction between security and accessibility.
2Object-affected harmful factors
If parental control software blocks specific forbidden objects, then exposure to malicious content is reduced, but the system complexity increases
Solution Approach 1:
The system employs automated clustering algorithms that self-organize user profiles into groups based on their connections and characteristics. This self-service mechanism automatically identifies suspicious objects without requiring manual configuration, thereby reducing system complexity while effectively reducing exposure to malicious content.
Solution Approach 2:
The system uses feedback from user interactions and connection patterns to continuously refine its identification of suspicious objects. By monitoring how users interact with different objects and using this feedback to update clustering results, the system dynamically adapts to new threats without increasing complexity.
Data Source
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AI summary
Disclosed are systems and methods for limiting access of a user profile to dangerous content in a social network service. The described system produces a social graph for a given user profile in the social network service, and identifies clusters of objects (e.g., other user profiles, contents) within the social graph. The described system analyzes whether certain objects in the social graph should be characterized as suspicious based on their clustering and on a database of known forbidden objects. The described system may further learn and add unknown objects to the database of forbidden objects.