Browser Event Logging for Bot Detection via Timing Analysis
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Solution Overview
Problem
Existing online security measures struggle to effectively differentiate between human and bot activity in browser sessions, particularly in online forms, leading to vulnerabilities in network and form security.
Innovation Solution
A method and apparatus that initiate an event logging procedure on a webpage, listen to specific event types, measure timing between events, aggregate these events and timing into an array, and transmit this data to a server to determine whether the activity is human or bot-related.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional online security measures are used to detect bot activity, then implementation is simple, but detection accuracy between human and bot activity is poor
Solution Approach 1:
The patent segments bot detection into multiple independent event types (mouse events, keyboard events, form interaction events, navigation events) that are collected and analyzed separately. Each event type provides specific behavioral indicators that, when combined, enable accurate differentiation between human and bot activity without requiring a monolithic complex system
Solution Approach 2:
The patent introduces JavaScript-based event logging code as an intermediary layer between the user interface and the server. This intermediary captures detailed interaction events locally in the browser and transmits them to the server for analysis, enabling sophisticated detection without complicating the core security infrastructure
2Measurement precision
If detailed event logging is implemented to improve detection accuracy, then bot detection precision increases, but data processing volume and transmission load increase
Solution Approach 1:
The patent extracts only the essential and discriminatory event features needed for bot detection from the complete set of possible browser events. By selecting specific event types (mouse movements, clicks, keyboard input patterns, form field interactions) and their temporal relationships, the system achieves high detection accuracy while minimizing the volume of data that needs to be transmitted and processed
Solution Approach 2:
The patent implements partial monitoring of event types by focusing on the most discriminative events for bot detection rather than logging all possible browser activities. This selective approach captures sufficient behavioral patterns to distinguish bots from humans while reducing overall data generation and transmission requirements
Data Source
AI summary
Systems, methods, apparatuses, and computer program products for online form logging malicious or bot activity detection. The method may include, initiating an event logging procedure on a webpage. The method may also include listening to one or more event types via the form detection procedure on the webpage. The method may further include measuring a timing between each of the one or more events. In addition, the method may include aggregating the one or more events and the timing between each of the one or more events into an array. Further, the method may include transmitting the array to a server device to determine, based on the array, whether there is human activity or bot activity.