Movement Pattern Authentication for Secure VR Access
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Solution Overview
Problem
Existing authentication methods lack robust security measures to prevent unauthorized access to devices, applications, and services, particularly in virtual reality environments.
Innovation Solution
Utilizing virtual reality technologies to record and authenticate user movement patterns, incorporating timing and frequency, and integrating these patterns into authentication processes to introduce additional layers of security and entropy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional authentication methods (username and password) are used, then ease of operation is improved, but security is worsened
Solution Approach 1:
The authentication process is segmented into multiple independent factors: device information verification, movement pattern recognition, and timing/frequency analysis. Each segment contributes to the overall security without compromising usability, as the system evaluates multiple dimensions of user behavior rather than relying on a single password entry step.
Solution Approach 2:
The patent replaces the mechanical keyboard input system (typing passwords) with an optical/motion-based recognition system that captures and analyzes user movement patterns through sensors and computer vision. This substitution maintains ease of operation while dramatically improving security by capturing biometric behavioral data that is much harder to steal or replicate.
2Reliability
If movement pattern recognition is added to authentication, then security is improved, but device complexity is worsened
Solution Approach 1:
The system uses universal smartphone components (camera, accelerometer, gyroscope, processor) that already exist in modern devices. These multi-functional components serve both standard application purposes and authentication functions, avoiding the need for specialized hardware and minimizing the increase in device complexity while still enabling sophisticated movement pattern analysis.
Solution Approach 2:
The authentication system leverages the device's own sensors and processing capabilities to perform self-analysis of movement patterns. The device uses its built-in resources to capture, process, and validate authentication data without requiring external authentication servers or additional specialized hardware, thereby reducing system complexity while maintaining high security standards.
3Reliability
If multiple authentication factors are implemented, then security is improved, but ease of operation is worsened
Solution Approach 1:
The system performs preliminary analysis of device information and movement patterns in the background during normal device usage. By the time authentication is required, much of the data collection and initial processing has already occurred, allowing the actual authentication step to be quick and seamless. This preliminary action ensures that multiple authentication factors are evaluated without creating a lengthy or complex user experience.
Data Source
AI summary
A computer-implemented method includes presenting one or more categories of movement patterns. The computer-implemented method includes recording a movement pattern of a user, where the movement pattern is associated with the one or more categories of movement patterns. The computer-implemented method includes authenticating the recorded movement pattern is correct. The computer-implemented method includes associating the authenticated recorded movement pattern with at least one of a device, application, and web-based service.