Confidence-Based Network Device Provisioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for connecting computing devices to secure networks often require user intervention and lack efficient automated processes for authorizing new devices, which can lead to security vulnerabilities and increased user effort.
Innovation Solution
A confidence-based authorization process that uses a series of phases to assess the likelihood of a device's authorization through a confidence score, allowing automated connection without user input by comparing device-specific data against predefined thresholds, thereby preventing unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automated connection processes are implemented, then user effort is reduced, but security risks increase due to potential unauthorized access
Solution Approach 1:
The system performs preliminary actions by collecting device data, generating confidence scores, and establishing authorization criteria before the actual connection is made. This advance assessment ensures security validation occurs automatically without requiring user intervention during the connection moment, thus reducing user effort while maintaining security through pre-validated authorization.
2Reliability
If manual authorization processes are used, then security is maintained through user control, but user effort and time consumption increase
Solution Approach 1:
The system implements self-service by enabling devices to automatically authenticate themselves through confidence score evaluation. The network system autonomously assesses device credibility, compares confidence scores against thresholds, and grants or denies access without requiring user intervention. This self-authorized process maintains security through automated validation while eliminating time-consuming manual authorization steps.
3Reliability
If confidence score thresholds are set high, then security is improved by preventing unauthorized access, but device connectivity is reduced
Solution Approach 1:
The system applies dynamics by making confidence score thresholds adjustable and adaptable rather than fixed. Thresholds can be dynamically configured based on network security requirements, device types, and environmental contexts. This dynamic approach allows the system to optimize the balance between security and connectivity by raising thresholds when security is prioritized and lowering them when device integration is the goal, thus preventing unauthorized access while maintaining productive connectivity.
Data Source
AI summary
Techniques for establishing a data connection are described. In an example, a computer system receives, from a second device of a computer network, first data associated with a first device and second data associated with the second device. The first device is not connected to the computer network. The computer system determines third data generated by one or more devices other than the first device and the second device and associated with at least one of: the first device, the second device, a user account, or the computer network. The computer system generates, based on the first data, the second data, and the third data, a confidence score indicating a likelihood of a user authorization to connect the first device to the computer network. The computer system sends, to the second device based on the confidence score, instructions associated with connecting the first device to the computer network.