Video Password Authentication Using ML for Secure User Login
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Solution Overview
Problem
Existing username and password authentication methods face a tradeoff between security and user convenience, often requiring complex passwords or additional hardware/software tokens, which can be cumbersome and prone to security attacks.
Innovation Solution
Implementing a video password authentication system using machine learning techniques to authenticate users based on motion and non-motion data from video inputs, allowing for secure and user-friendly identity verification without the need for complex passwords or additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional username and password authentication is used, then security can be maintained, but user convenience deteriorates due to complex passwords and additional hardware/software tokens
Solution Approach 1:
The patent replaces the mechanical system of hardware tokens and software applications with a camera-based video authentication system. The video password captures natural user movements and characteristics, eliminating the need for separate authentication devices or complex password management while maintaining security through biometric-like verification of motion patterns and visual characteristics
2Reliability
If complex passwords are required for security, then security improves, but ease of operation deteriorates due to user burden
Solution Approach 1:
The patent changes the authentication parameters from static text passwords to dynamic video data comprising motion data and non-motion data. This transformation allows the system to capture complex security information including movement patterns, timing, and visual characteristics while the user simply performs natural actions, eliminating the burden of remembering complex passwords
3Reliability
If video password authentication with machine learning is implemented, then security and accuracy improve, but device complexity increases
Solution Approach 1:
The patent segments the authentication system into distinct functional modules: video capture, motion data extraction, non-motion data extraction, machine learning model processing, and authentication decision-making. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by clearly defining the role and interface of each module
Data Source
AI summary
Systems and methods of video password based user authentication via machine learning techniques are disclosed. In one embodiment, an exemplary computer-implemented method may comprise: receiving a request to register a video password from a first user; establishing at least one user-specific authentication criterion for the first user based on first video password data; receiving a login attempt from a second computing device associated with a second user who submits to be the first user, the login attempt comprising second video password data; utilizing a trained video password authentication machine learning model to determine a first comparison result and a second comparison result based on the first and second video password data, and accepting or rejecting the login attempt based on at least one of the first comparison result and the second comparison result.