Multi-factor Identity Fingerprinting for Continuous Authentication
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Solution Overview
Problem
Current authentication methods rely heavily on passwords and physical tokens, which are vulnerable to theft and hacking, and do not provide continuous verification of user identity, leading to potential identity theft and security breaches.
Innovation Solution
Implementing multi-factor identity fingerprinting that tracks and aggregates user behavior patterns, preferences, and interactions across various systems to generate a unique identity fingerprint, which can be used for continuous authentication without interrupting user sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication methods (passwords and physical tokens) are used, then authentication can be performed, but security is vulnerable to theft and hacking
Solution Approach 1:
The patent replaces mechanical/password-based authentication with biometric and behavioral authentication. Instead of relying on memorized credentials or physical tokens that can be stolen, the system uses unique biological characteristics (fingerprint, retina scan) and behavioral patterns (typing speed, mouse movements) that are inherently difficult to replicate or steal.
Solution Approach 2:
The patent changes the authentication parameters from static (fixed passwords) to dynamic and continuous. Rather than a single login event, the system continuously monitors and compares multiple behavioral parameters during user interactions, updating the authentication state in real-time based on changing behavior patterns.
2Reliability
If continuous authentication is implemented, then security is improved, but user experience is degraded due to frequent interruptions
Solution Approach 1:
The authentication system serves itself by automatically monitoring user behavior without requiring explicit user action. The system continuously collects behavioral data in the background and autonomously compares it against established patterns, performing authentication verification without interrupting user workflows or requiring additional user input.
Solution Approach 2:
Instead of continuous interruption, the system employs periodic sampling of user behavior at strategic points during interactions. Authentication checks occur at natural breakpoints in user workflows (such as after a series of actions or at defined time intervals) rather than constantly, maintaining a balance between security verification and user experience.
3Reliability
If multiple authentication factors are collected, then authentication robustness is improved, but system complexity increases
Solution Approach 1:
The patent segments authentication into distinct factors: biometric factors (fingerprint, retina scan) and behavioral factors (typing speed, mouse movements, navigation patterns). Each factor is collected, processed, and evaluated independently through separate modules, making the complex authentication system manageable and scalable while maintaining robustness through multiple independent verification layers.
Data Source
AI summary
A security fingerprint architecture is disclosed. A security fingerprint comprises one or more behavioral factors which store a history of events associated with one or more users. The data in the security fingerprint is exposed by one or more modes, each of which determines the conditions that data in the security fingerprint may be accessed. Security fingerprints support a number of primitive operations that allow set operations to be performed. Security fingerprints may be used in for authentication, advertising, and other operations either alone, or in conjunction with third party data sources. An exemplary platform of security fingerprints built upon a cellular infrastructure is also disclosed.