Adaptive CAPTCHA Delivery for Authentication Security
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Solution Overview
Problem
Conventional CAPTCHA security tests are inefficient as they require manual input, reducing processing efficiency and are vulnerable to automated cracking, especially since they are not selectively delivered based on attack type.
Innovation Solution
An identity authentication method that determines if an operation is a machine attack by analyzing network environment and user behavior data, delivering a CAPTCHA only when necessary, and using a CAPTCHA of varying types based on attack likelihood to enhance security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a CAPTCHA security test is used to determine whether a human or a machine is entering authentication information, then authentication security is improved, but user operations become increasingly complex and processing efficiency of authentication is reduced
Solution Approach 1:
The system dynamically adjusts whether to deliver a CAPTCHA based on real-time analysis of network environment information and user behavior data. Instead of always presenting a CAPTCHA, the system determines the likelihood of a machine attack and selectively delivers CAPTCHAs only when necessary, making the authentication process adaptive rather than static
Solution Approach 2:
The system changes the parameter of CAPTCHA delivery from a fixed state (always delivered) to a variable state (delivered conditionally based on attack likelihood assessment). This parameter change allows the system to balance security requirements with processing efficiency by adjusting CAPTCHA delivery based on analyzed parameters such as network environment and user behavior patterns
2Reliability
If a conventional CAPTCHA including a small character image and an entry box is used, then authentication security is improved to a particular degree, but an illegal intruder may directly pull an image of a CAPTCHA very easily by using a technical solution, and then perform cracking by using an automaton
Solution Approach 1:
The system performs preliminary analysis of network environment information and user behavior data before delivering a CAPTCHA. By assessing the likelihood of a machine attack in advance, the system can deliver a CAPTCHA proactively when suspicious activity is detected, rather than reactively after an attack attempt
Solution Approach 2:
The system introduces an intermediary analysis layer that examines network environment information and user behavior data between the authentication request and CAPTCHA delivery. This intermediary assessment acts as a mediator to determine whether a CAPTCHA should be delivered, adding an extra layer of security evaluation before the actual authentication challenge
3Reliability
If a CAPTCHA is delivered in all cases to ensure security, then authentication security is improved, but user operations are made more complex and processing efficiency is reduced
Solution Approach 1:
The system dynamically determines whether to deliver a CAPTCHA based on real-time analysis of user behavior data and network environment information. This dynamic approach allows the system to adapt to each user's behavior pattern, delivering CAPTCHAs only when the analysis indicates a machine attack is likely, rather than applying a static rule to all users
Solution Approach 2:
The system uses the user's own behavior data and network environment information to automatically determine whether a CAPTCHA should be delivered. By analyzing the user's authentication patterns, device characteristics, and network context, the system makes an automated decision about CAPTCHA delivery, reducing manual intervention while maintaining security
Data Source
AI summary
A method may be performed using a server. The method may include receiving an identity authentication request associated with a user, generating authentication information based on the identity authentication request, and generating candidate information based on the authentication information such that the authentication information is a subset of the candidate information. The candidate information may be displayed at a randomly selected location. The user may provide input through a graphic input interface to select the authentication information from among the candidate information.