AI Behavioral Authentication via Moving Object Selection
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Solution Overview
Problem
Current authentication methods are inconvenient and prone to identity theft, as they require users to remember passwords and respond to multiple security layers, which can be cumbersome and fail due to issues like non-operational devices or stolen information.
Innovation Solution
A method and system using artificial intelligence that renders a graphical user interface with moving objects, where users select objects to form patterns, with confidence scores determined based on subconscious choices, eliminating the need for passwords and extra security layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication methods (passwords, OTP, biometric) are used, then security is improved, but user convenience and authentication speed deteriorate
Solution Approach 1:
The system uses the user's own subconscious behavioral patterns as the authentication mechanism. The user's natural interaction with moving objects on the screen creates a unique selection sequence that serves as the authentication credential, eliminating the need for external security layers like passwords or OTP while maintaining convenience.
Solution Approach 2:
The patent replaces traditional mechanical authentication systems (password entry, biometric scanning, OTP verification) with an AI-based system that analyzes subconscious behavioral patterns. The AI processes the user's natural screen interaction patterns to authenticate identity, substituting complex mechanical security layers with intelligent behavioral analysis.
2Measurement precision
If multiple security layers are added, then authentication accuracy is improved, but authentication time and complexity increase
Solution Approach 1:
The system performs preliminary training during the user onboarding process, where the AI learns and stores the user's subconscious selection patterns in advance. This preliminary action creates a reference profile that enables rapid authentication later without requiring multiple verification steps, thus reducing authentication time while maintaining accuracy.
Solution Approach 2:
The patent replaces time-consuming multi-layer authentication processes with a single-pass behavioral analysis system. The AI evaluates the user's subconscious selection sequence in real-time and makes an authentication decision without requiring additional verification steps, significantly reducing authentication time while maintaining high accuracy.
3Reliability
If CAPTCHA with distorted characters is used, then security against automation is improved, but user identification accuracy deteriorates
Solution Approach 1:
Instead of presenting distorted characters that users must identify (traditional CAPTCHA approach), the system inverts the approach by presenting moving objects that users naturally select based on subconscious patterns. The authentication is based on the selection sequence itself rather than the ability to identify distorted elements, eliminating identification errors while maintaining security against automation.
Solution Approach 2:
The patent replaces the optical character recognition-based CAPTCHA system with an AI-based behavioral analysis system. Instead of relying on users to accurately identify distorted characters, the system analyzes the user's natural interaction patterns with moving objects, providing a more accurate and user-friendly authentication method that is equally effective against automation.
Data Source
AI summary
A method and a system for authenticating users by implementing artificial intelligence techniques is provided. A graphical user interface (GUI) is rendered on a computing device of a user by a server. The GUI displays objects in random motion. The objects are selected in a sequential manner by the user to form a pattern. With each selection of the object, a corresponding confidence score is determined that is based on a set of factors. Further, the selected object becomes static and the remaining objects that are yet to be selected continue to move in random motion. On forming the pattern, the aggregate of confidence scores is determined to authenticate the user.