Biometric Verification via Environmental Parameter Analysis
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Solution Overview
Problem
Existing methods for differentiating legitimate human-initiated web requests from malicious requests are intrusive, complex, and do not effectively mitigate distributed denial-of-service (DDoS) attacks, as they rely on browser detection techniques that can be bypassed by Internet bots.
Innovation Solution
A biometric verification method that analyzes environmental parameters from client machines, such as mouse movements and keystrokes, to determine if a human user is making a request, using APIs and embedded scripts to validate the presence of a human client, and selectively provides services based on this determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CAPTCHA is used to differentiate human users from bots, then human detection capability is improved, but user experience deteriorates due to intrusiveness and complexity
Solution Approach 1:
The system performs preliminary human detection by analyzing environmental parameters (mouse movements, keystrokes, gestures) before the user encounters any challenge. This allows the system to identify human users in advance, so that CAPTCHA is only presented when truly necessary, thereby maintaining security while improving user experience for legitimate users.
Solution Approach 2:
The patent replaces the mechanical interaction-based CAPTCHA system with a biometric-based detection system that analyzes environmental parameters such as mouse movement patterns, keystroke dynamics, and gesture recognition. This substitution maintains human detection capability while eliminating the need for users to solve puzzles or complete challenging tasks.
2Ease of manufacture
If traditional browser detection techniques are used, then implementation simplicity is improved, but effectiveness deteriorates because bots can bypass them
Solution Approach 1:
The system transitions from analyzing traditional browser characteristics (user agent strings, canvas rendering) to analyzing environmental parameters and biometric data (mouse movements, keystrokes, gestures, facial expressions). This dimensional shift from software-based to behavior-based and biometric-based detection creates a new detection space that bots cannot easily replicate, thereby improving effectiveness while maintaining implementation feasibility through API integration.
3Reliability
If CAPTCHA is deployed to mitigate DDoS attacks, then security is improved, but service availability deteriorates because legitimate users are blocked
Solution Approach 1:
The system performs preliminary analysis of environmental parameters to identify human users before they submit requests that would trigger CAPTCHA. By pre-identifying legitimate human users through their unique behavioral patterns, the system allows them to access services without interruption while blocking bot traffic, thereby maintaining both security and service availability.
Solution Approach 2:
The system continuously monitors environmental parameters and adjusts its filtering decisions based on real-time analysis of user behavior patterns. This feedback mechanism allows the system to dynamically distinguish between legitimate users and bots, maintaining security while minimizing false positives that would block legitimate traffic and preserve service availability.
Data Source
AI summary
Provided are methods and systems for biometric verification of a human Internet user. A method for biometric verification of a human Internet user comprises receiving, from a client machine, a web request for a service and environmental parameters associated with the client machine. The method further comprises determining whether the environmental parameters are indicative of the human Internet user. Based on the determination, the service is selectively provided to the client machine in response to the web request.