Dynamic Digital Media Authentication Using Environmental Risk Metrics
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Solution Overview
Problem
Conventional authentication systems are vulnerable to malicious attacks and hacking, as they rely on static user credentials and images, which can be easily deceived by fraudulent means, leading to security breaches.
Innovation Solution
A system that evaluates multiple digital media recordings over time to detect features such as background noises, objects, and light direction, using AI models to generate risk metrics and determine the probability of user authenticity, thereby enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional authentication systems use static user credentials and images, then the authentication process is simple and fast, but the system becomes vulnerable to malicious attacks and hacking
Solution Approach 1:
The patent transforms static authentication credentials into dynamic multimedia recordings captured in real-time. Instead of using fixed passwords or images, the system requires users to provide video and audio recordings that inherently change with each authentication attempt, making stolen credentials obsolete and significantly improving security against replay attacks
Solution Approach 2:
The patent embeds multiple layers of verification within the authentication process. It nests environmental feature detection (background noises, objects, light direction) inside the multimedia recording analysis, and further nests AI-based risk metric evaluation inside the authentication decision-making process, creating a fortified multi-layered security system
2Measurement precision
If the system requests multiple media recordings and performs AI-based analysis, then authentication accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary analysis by detecting environmental features (background noises, objects, light direction) during the recording capture phase itself. This allows the system to prepare risk indicators before the actual authentication decision is made, reducing the computational burden and processing time during the critical authentication moment
Solution Approach 2:
The patent divides the authentication analysis into separate modular components: environmental feature detection, risk metric generation, and final authentication decision. This segmentation allows each component to be optimized independently and processed in parallel, improving overall processing efficiency while maintaining high authentication accuracy
3Reliability
If the system detects environmental features like background noises and objects, then the ability to detect fraudulent attempts improves, but the device complexity and processing requirements increase
Solution Approach 1:
The patent introduces AI-based risk determination models as intermediaries between the raw environmental feature detection and the authentication decision. These models act as mediators that automatically interpret complex environmental data (background noises, objects, light direction) and translate them into meaningful risk metrics, reducing the complexity burden on the overall system while enhancing fraud detection capability
Data Source
AI summary
Systems and methods for digital media-based user authentication are disclosed herein. In some aspects, the system may receive an authentication request. The system may transmit a user verification request based on the authentication request. The system may receive media recordings in response to the user verification request. The system may detect one or more features in the media recordings. The system may generate a plurality of risk metrics for the user based on generating risk metrics for the one or more features. The system may determine an authentication probability based on the plurality of risk metrics.