Behavioral Bio Fingerprinting for AI-Based User Authentication
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Solution Overview
Problem
Existing user-interfacing systems lack the necessary information to effectively authenticate and authorize users, particularly in cases where malicious intent may disrupt system operation and security.
Innovation Solution
A system that collects and analyzes behavioral data from a user's mobile device and in-house AI models to perform a series of tests, using AI models with progressive learning algorithms and neural networks to determine user authenticity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If systems collect and analyze behavioral data from multiple sources using AI models, then user authentication accuracy and system security are improved, but device complexity and information processing requirements increase
Solution Approach 1:
The system segments behavioral data collection into multiple independent modules: device information collection from mobile devices, browsing history collection, social media activity collection, and shopping behavior collection. Each module operates independently and feeds into the AI analysis engine, allowing the system to manage complexity through modular architecture while maintaining high authentication accuracy.
Solution Approach 2:
An AI model serves as an intermediary between raw behavioral data from multiple sources and the authentication decision. The AI model aggregates and analyzes data from device information, browsing history, social media activity, and shopping behavior, transforming fragmented data into comprehensive user profiles that enable accurate authentication without requiring direct integration of all data sources.
2Reliability
If systems research and analyze prospective users before granting access, then system security is improved, but loss of time and processing duration increase
Solution Approach 1:
The system performs preliminary behavioral analysis by continuously collecting and storing user data from multiple sources (device information, browsing history, social media activity, shopping behavior) before authentication is needed. This pre-collected data is ready for rapid analysis when a user requests access, enabling security verification without time-consuming real-time research.
Solution Approach 2:
Traditional manual or rule-based user research methods are replaced with AI-powered automated analysis. The AI model processes behavioral data from multiple sources simultaneously and generates authentication decisions rapidly, substituting time-consuming mechanical research processes with efficient computational analysis that maintains high security standards.
Data Source
AI summary
Methods and systems for providing a behavioral bio fingerprinting analysis system. The system includes an electronic system with a receiver for receiving a request from a user's mobile device. The mobile device includes an electronic file for storing behavioral data. The system further comprises an in-house AI model for retrieving behavioral data about a user. The system further includes a processor for generating an AI model that retrieves the behavioral data from the user's mobile device and form related AI systems. The AI model may store the behavioral data and may run a behavioral analysis. The behavioral analysis may include a series of tests. The user may be authenticated. Access into the system may be granted to the user upon passing the series of tests.