Network Resource Assignment via User Association Analysis
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Solution Overview
Problem
Existing systems face challenges in efficiently identifying the appropriate user group for accessing network resources, leading to potential unauthorized access, increased maintenance costs, and temporal delays due to the manual and time-consuming process of searching for optimal user groups in large organizational networks.
Innovation Solution
A central server automatically identifies closely associated users based on shared characteristics and analyzes user groups to recommend the most appropriate group that provides the shortest network path to the requested resource, reducing the need for unnecessary new user groups and enhancing security and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual process is used to search for optimal user groups, then flexibility and control are maintained, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system enables self-service by automatically analyzing user characteristics, identifying associated users, and recommending optimal user groups without requiring manual administrative intervention. The central server autonomously performs the complete assignment process based on predefined criteria and associations.
Solution Approach 2:
The patent replaces the manual mechanical process of searching and assigning users to groups with an automated computational system. The central server uses algorithms to analyze user data, identify associations, and determine optimal group assignments, substituting human effort with automated information processing.
2Ease of manufacture
If existing user groups are reused for user assignment, then maintenance time and costs are reduced, but the risk of unauthorized access to inappropriate resources increases
Solution Approach 1:
The system incorporates feedback mechanisms by analyzing the characteristics of associated users and their existing group memberships. This feedback loop enables the system to learn from existing assignments and make intelligent recommendations that balance resource reuse with appropriate access control, ensuring security while reducing maintenance overhead.
Solution Approach 2:
The patent changes the parameters of user group assignment by introducing dynamic analysis of user associations and characteristics. Instead of static assignment rules, the system adjusts group recommendations based on real-time analysis of user relationships, shared characteristics, and access patterns, optimizing both security and maintenance efficiency.
3Adaptability or versatility
If multiple user groups provide access to the same network resource, then access flexibility is improved, but identifying the appropriate user group becomes more complex
Solution Approach 1:
The system segments the complex task of user group identification into distinct analytical components: analyzing user characteristics, identifying associated users, evaluating group memberships, and ranking recommendations. This segmentation simplifies the overall process by breaking down the complex decision-making into manageable steps that can be automated.
Solution Approach 2:
The patent adds another dimension to user group selection by considering multiple criteria simultaneously - user associations, shared characteristics, existing memberships, and access patterns. This multi-dimensional approach transforms the simple choice among multiple groups into an intelligent recommendation system that evaluates options across several dimensions, reducing complexity through structured analysis.
Data Source
AI summary
A system includes a plurality of shared network resources and a central server connected by a network. The central server receives from a first user a request for accessing a network resource. The central server identifies a plurality of user groups the first user is part of and determines a number of other users from the identified user groups who have the closest association with the first user. For each closely associated user of the first user, the central server simulates access to the requested network resource by the respective user based on a user group that provides to the other user access to the network resource. Based on results of the simulating, the central server determines a user group that provides a closest network path to the network resource and generates a recommendation to add the first user to the determined user group.