Purpose:
We are seeking a comprehensive dataset that includes mouse movement data for the purpose of distinguishing between human users and automated bots in web-based CAPTCHA systems. The goal is to develop and refine machine learning models that can accurately identify bot-like behavior based on mouse interaction patterns, enhancing the security and effectiveness of CAPTCHA systems.
Dataset Requirements:
Mouse Movement Data: Raw data capturing mouse coordinates, velocity, acceleration, and direction changes as users interact with a web page.
Click Event Data; Records of click positions, timing, and frequency to analyze the decision-making process and interaction speed.
Human vs. Bot Interaction: Clear distinction between data generated by human users and data generated by automated scripts (bots). This will allow for supervised learning and model training.
Time-Series Data: Sequential data capturing the timestamp of each mouse event to analyze the flow and pattern of movements.
Behavioral Biometrics: Data capturing user-specific behaviors that might indicate human-like randomness or bot-like precision in interactions.
Variety of Interactions: Diverse interaction scenarios, including different types of CAPTCHA challenges (e.g., image recognition, text entry) and general web browsing activities.
submitted by /u/RareNeedleworker832
[link] [comments]
