Biometric Identity Token for Spoof-Resistant Authentication
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Solution Overview
Problem
Current security systems face challenges in effectively protecting user identities from malicious attacks, particularly in online environments where data breaches and unauthorized access are common.
Innovation Solution
A security platform architecture that utilizes a combination of biometric analytics to create a unique identity token for each individual, incorporating factors like human behavior, motion analytics, physical characteristics, and device usage patterns, making it difficult to spoof or hack.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security systems are used for user identification, then the system is easier to implement and operate, but the system becomes vulnerable to spoofing and hacking attacks
Solution Approach 1:
The patent combines multiple biometric analytics (facial recognition, voice recognition, behavioral patterns, device usage patterns) into a unified identity token system. This merging of multiple security factors creates a comprehensive authentication mechanism that is resistant to spoofing while maintaining systematic operation through centralized token management.
Solution Approach 2:
The identity token is constructed as a composite security mechanism integrating diverse biometric factors (physical characteristics, behavioral patterns, motion analytics). This composite approach similar to composite materials provides enhanced security properties that resist various attack vectors while the token itself serves as a unified authentication object.
2Measurement precision
If multiple biometric factors are collected and analyzed, then the confidence in user identity verification increases, but the time and computational resources required increase
Solution Approach 1:
The system performs preliminary biometric analysis during device usage and interaction, continuously gathering and analyzing behavioral patterns, device usage patterns, and other biometric data before formal authentication is required. This preliminary action allows the system to pre-compute confidence scores and reduce authentication time when actual verification is needed.
Solution Approach 2:
The biometric analytics operate continuously in the background during normal device usage, constantly updating the identity token with new behavioral and usage data. This continuous analysis ensures that when authentication is required, the system already has current and comprehensive biometric information, eliminating the need for lengthy authentication processes.
3Reliability
If dynamic biometric tokens are used instead of static passwords, then security against malware and hacking is improved, but the system complexity and difficulty of operation increase
Solution Approach 1:
The biometric authentication system operates automatically without requiring active user participation. The device continuously collects biometric data, generates identity tokens, and performs authentication actions autonomously. Users simply need to interact with the device as normal, and the biometric security system handles verification in the background, making the process as easy as conventional authentication while providing superior security.
Data Source
AI summary
A security platform architecture is described herein. A user identity platform architecture which uses a multitude of biometric analytics to create an identity token unique to an individual human. This token is derived on biometric factors like human behaviors, motion analytics, human physical characteristics like facial patterns, voice recognition prints, usage of device patterns, user location actions and other human behaviors which can derive a token or be used as a dynamic password identifying the unique individual with high calculated confidence. Because of the dynamic nature and the many different factors, this method is extremely difficult to spoof or hack by malicious actors or malware software.