Trusted Computing Network for Human-Machine Authentication
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Solution Overview
Problem
Current CAPTCHA techniques are vulnerable to various attacks and easy to crack, leading to poor user experiences and security threats in Web services, as advancements in character segmentation and machine learning algorithms have compromised their effectiveness.
Innovation Solution
The method employs Trusted Computing technology over a trusted network to distinguish humans from machines by analyzing network access request frequencies, using a Decision Point to verify identity certificates and issue authorization credentials, thereby controlling access to network services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional CAPTCHA techniques (text, image, sound) are used to distinguish humans from machines, then authentication security is provided, but they become vulnerable to attacks and easy to crack due to advancements in character segmentation and machine learning algorithms
Solution Approach 1:
The patent changes the fundamental parameter of authentication from static challenge-response (CAPTCHA) to dynamic behavior analysis. Instead of relying on users to solve puzzles, the system monitors request frequency, response time, and access patterns over time, transforming the authentication mechanism from a single-point challenge to a continuous behavioral assessment that adapts to detected anomalies
Solution Approach 2:
The patent introduces a trusted third-party authentication server as an intermediary between the user terminal and network service provider. This mediator performs the complex behavioral analysis and frequency monitoring, issuing authentication credentials that the network service provider can verify without having to implement complex detection algorithms themselves, thus distributing the security burden
2Object-affected harmful factors
If CAPTCHA challenges are presented to users for authentication, then machine attacks are reduced, but user experience deteriorates due to the need to solve puzzles and additional verification steps
Solution Approach 1:
The system performs automatic behavioral analysis and authentication without requiring user participation in puzzle-solving. The authentication server autonomously monitors request patterns, analyzes behavior metrics, and makes authentication decisions based on collected data, eliminating the need for users to actively engage with CAPTCHA challenges while maintaining security
Solution Approach 2:
The system performs preliminary behavioral analysis and frequency monitoring before actual authentication is required. By continuously collecting and analyzing access patterns in advance, the system can quickly verify legitimate users without requiring them to solve puzzles at the moment of authentication, as the behavioral baseline is already established
3Reliability
If Trusted Computing technology with frequency analysis is implemented to distinguish humans from machines, then security against unauthorized access is enhanced, but system complexity increases due to the need for Decision Points and authorization credential verification
Solution Approach 1:
The trusted third-party authentication server performs multiple functions: behavioral analysis, frequency monitoring, authentication credential issuance, and verification support. This multi-functional design consolidates what could be separate complex components into a single versatile system that handles both security enforcement and authentication management
Solution Approach 2:
The patent extracts the complex behavioral analysis and authentication logic from the network service provider's system and places it in a dedicated trusted third-party authentication server. This separation allows the service provider to maintain a simple verification process while the authentication server handles the sophisticated frequency analysis and decision-making algorithms
Data Source
AI summary
A method and an apparatus for distinguishing humans from computers and for controlling access to network services. One intended application of the method is a CAPTCHA technique, deployed using a shared Trusted Computing technology over a trusted network of a user terminal, a network server, and a Trusted Party, any of which may be at a Decision Point. The method distinguishes a human user making a legitimate request for network access from a programmed computer making undesired requests, by detecting unusually high network access request frequencies made by an identifiable user and/or a trusted module from the user terminal. The CAPTCHA function is further used to improve the method for controlling access to network services. The information transmitted between the members of the trusted network may be encrypted.