Browser Page Alteration for Verifying Non-Human Traffic
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Solution Overview
Problem
Existing technologies struggle to effectively identify and verify illegitimate non-human users accessing content, particularly bots, which can fraudulently inflate impression counts and clicks, leading to financial losses and reduced algorithm quality.
Innovation Solution
A computer-implemented method alters browser pages with decoy advertisements and redirect pages to verify bots by exploiting behavioral differences between humans and bots, using techniques such as CAPTCHAs, invisible links, and hidden form fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CAPTCHA challenges are presented to users, then bot traffic is blocked, but legitimate user experience is degraded
Solution Approach 1:
The system applies different verification qualities to different traffic sources. Human users experience a smooth, natural interaction flow, while bot traffic is subjected to sophisticated verification challenges. This local differentiation allows the system to maintain high usability for legitimate users while effectively blocking bots.
Solution Approach 2:
The system introduces an intermediary verification layer that analyzes traffic patterns, device characteristics, and behavior metrics to determine whether to present challenges. This intermediary layer filters traffic before it reaches the application, blocking bots without exposing them to users and maintaining natural interaction flows for legitimate users.
2Measurement precision
If sophisticated verification challenges are implemented, then bot detection accuracy is improved, but processing time and system complexity increase
Solution Approach 1:
The verification system is segmented into multiple independent analysis components that evaluate different aspects of traffic behavior (device characteristics, interaction patterns, biometric data). Each segment operates independently and contributes to the overall verification decision, allowing sophisticated detection without creating a monolithic complex system.
Solution Approach 2:
The system performs preliminary analysis of device characteristics and behavior patterns before presenting verification challenges. By pre-evaluating traffic sources and identifying suspicious patterns early, the system can apply targeted verification only when necessary, reducing overall system complexity while maintaining high detection accuracy.
3Reliability
If multiple verification methods are used, then verification reliability is improved, but implementation complexity increases
Solution Approach 1:
The verification system is designed as a universal platform that can implement multiple verification methods (device fingerprinting, behavior analysis, biometric verification) through a single integrated architecture. This multi-functional design allows the system to adapt different verification approaches based on traffic patterns without requiring separate implementation systems for each method.
Solution Approach 2:
The system dynamically adjusts verification parameters and methods based on analyzed traffic characteristics. Rather than implementing all verification methods simultaneously with fixed complexity, the system changes verification parameters adaptively, applying only the necessary level of verification for each traffic source, thereby reducing implementation complexity while maintaining reliability.
Data Source
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AI summary
The present invention provides improved techniques that can be used to verify illegitimate non-human users that are accessing content. For example, a method of verifying a non-human user of a computerized device may comprise receiving information identifying a potential non-human user of a computerized device, altering a browser page to be used by the potential non-human user, and verifying whether or not the potential non-human user is an actual non-human user based on a behavior of the potential non-human user with the altered browser page.