Metaverse Authentication via Behavioral Biometrics and Contextual Queries
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Solution Overview
Problem
Authentication in the metaverse is challenging due to its decentralized nature, posing risks such as identity theft and coercion during financial transactions.
Innovation Solution
A computer system that creates an analytical engine to track user activities within and outside the metaverse, a query engine to generate questions based on these activities, and an authentication engine to verify user responses, utilizing multi-factor authentication including audio and visual challenges to ensure free will.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional authentication methods are used in the metaverse, then ease of operation is improved, but reliability deteriorates due to decentralized nature and identity theft risks
Solution Approach 1:
The patent introduces an authentication system that acts as an intermediary between users and metaverse transactions. This system analyzes user behavior patterns, device characteristics, and transaction contexts to verify identities without requiring users to manually prove their identity, thus maintaining ease of operation while improving reliability through automated behavioral biometrics and multi-factor verification
2Reliability
If multi-factor authentication with behavioral analysis is implemented, then reliability is improved, but device complexity increases
Solution Approach 1:
The authentication system performs self-service by automatically collecting behavioral data, analyzing user patterns, and making authentication decisions without requiring complex user interaction or manual configuration. The system autonomously monitors device characteristics, analyzes transaction behaviors, and adjusts authentication requirements based on risk assessment, reducing the perceived complexity for users while maintaining high security
Solution Approach 2:
The system performs preliminary actions by continuously collecting and analyzing user behavioral data before actual transactions occur. It pre-establishes user profiles, device fingerprints, and behavioral baselines during normal usage, so that when a transaction occurs, authentication can be performed quickly by comparing against pre-analyzed data, reducing the complexity of real-time authentication decisions
Data Source
AI summary
An example computer system for authenticating a user can include: one or more processors; and non-transitory computer-readable storage media encoding instructions which, when executed by the one or more processors, causes the computer system to create: an analytical engine programmed to track activities of the user outside of a metaverse and within the metaverse; a query engine programmed to generate a series of questions for the user based upon the activities of the user outside of the metaverse and within the metaverse; and an authentication engine programmed to authenticate the user based upon responses to the series of questions provided by the user.