Web Page Event Observer for Non-Human Detection
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Solution Overview
Problem
Existing systems fail to effectively detect non-human presence during web page interactions, as CAPTCHAs can be solved by algorithms and random events can be annoying to users, necessitating a more robust method to differentiate human from non-human interactions.
Innovation Solution
A system and method that records events generated during content entry on a web page, using an event observer module to store events locally until submission, and an authored content module to associate these events with the content, allowing for analysis on a web server to determine the authenticity of user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CAPTCHA is used to verify human users, then security against automated programs is improved, but user experience deteriorates due to annoyance and limited placement options
Solution Approach 1:
The invention extracts the verification mechanism from fixed predetermined locations and embeds it throughout the web page via event observers that monitor user interactions across multiple elements, allowing verification to occur naturally during user navigation rather than at forced interruption points
Solution Approach 2:
The system introduces an event observer module as an intermediary that transparently monitors user interactions and collects event streams without directly blocking or interrupting user actions, allowing verification to occur in the background while maintaining natural user flow
2Reliability
If random events are inserted to detect automated programs, then detection capability is improved, but user experience deteriorates due to annoyance
Solution Approach 1:
The system uses the user's own natural interaction events (clicks, keystrokes, hovers) as the detection mechanism rather than introducing external random events, allowing the user's legitimate actions to serve as the verification data without adding intrusive elements
Solution Approach 2:
The system provides real-time analysis of event streams and uses the results to dynamically adjust verification requirements, providing feedback to both the user interface and the detection algorithm to improve accuracy while maintaining user experience
3Reliability
If event stream processing is used to detect human interactions, then detection accuracy is improved, but vulnerability to automated simulation increases
Solution Approach 1:
The system pre-registers specific event sequences and patterns that are characteristic of human behavior before they occur, establishing a baseline of expected human interaction patterns that can be compared against actual event streams to detect automated simulation attempts
Solution Approach 2:
The system dynamically adjusts the complexity and types of events being monitored based on the detected user behavior patterns, adapting the verification mechanism in real-time to maintain effectiveness against evolving automated simulation techniques
Data Source
AI summary
A web page that includes content form fields may be modified to include an event observer module and an authored content module. The authored content module adds a hidden “events observed” field to the form fields. Events generated during the authoring of content by a user are recorded by the event observer module. When the content is submitted from a client browser to the web server, the events generated during the authoring of the content are added to the events observed field and submitted with the content. The web server uses the events to determine a DOM of the web page and compare the observed DOM with a stored DOM for that web page and that particular interaction. The page structure may be optionally modified by the web server to enhance the analysis of the DOM comparison. The web server analysis facilitates detection of non-human content submission at a client browser.