Augmented User Authentication Using Ephemeral and Transient Features
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing user authentication systems rely heavily on permanent signals, such as facial features, which are ineffective when these signals are obscured, leading to authentication failures in scenarios like social distancing where faces are masked.
Innovation Solution
The system employs a computer-implemented method that captures images using a camera, compares recognized ephemeral and transient features with a baseline image, and determines a confidence level to authenticate the user, even when permanent signals are not available.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If permanent signals (facial features) are used for authentication, then authentication reliability is improved under normal conditions, but authentication fails when permanent signals are obscured (e.g., masked faces)
Solution Approach 1:
The authentication system segments the recognition signals into three categories: permanent signals (facial geometry), transient signals (clothing, accessories), and ephemeral signals (glasses, facial hair). This segmentation allows the system to selectively weight and combine different signal types based on availability, maintaining authentication capability when permanent signals are obscured by masks or other coverings.
Solution Approach 2:
The system dynamically changes the weighting parameters of different signal types based on their permanence and availability. Permanent signals are given higher weight when available, but the system adapts to use transient and ephemeral signals with adjusted weighting when permanent signals are obscured, thereby maintaining authentication reliability across varying conditions.
2Device complexity
If only permanent signals are used for authentication, then system simplicity is maintained, but authentication accuracy deteriorates when permanent signals are not available
Solution Approach 1:
The authentication system is designed to be universal by accepting multiple types of signals (permanent, transient, and ephemeral) for authentication. This multi-functionality allows the same system to operate effectively whether using only permanent signals under normal conditions or combining multiple signal types when permanent signals are obscured, thereby improving authentication accuracy without requiring separate systems.
Solution Approach 2:
The system performs preliminary classification and weighting of different signal types during the setup phase, establishing a hierarchy of signal reliability. This preliminary action enables the system to quickly determine which signals to use and how to weight them during authentication, maintaining both simplicity and accuracy without requiring complex real-time decisions.
3Reliability
If multiple signal types (ephemeral, transient, permanent) are combined for authentication, then authentication reliability is improved in obscured conditions, but system complexity increases
Solution Approach 1:
The system applies local quality by assigning different weights and reliability levels to different signal types based on their inherent characteristics. Permanent signals receive higher weight when available, while transient and ephemeral signals are weighted lower but become more important when permanent signals are obscured. This localized quality assignment manages complexity by not treating all signals equally but rather tailoring the analysis to each signal type's properties.
Solution Approach 2:
The system employs partial action by selectively processing only the necessary signal types based on availability. When permanent signals are available, the system may process only those or give them predominant weight, avoiding unnecessary processing of transient and ephemeral signals. This partial processing approach maintains reliability while reducing complexity by not always performing full multi-signal analysis.
Data Source
AI summary
A computer-implemented method includes: setting up, by a computing device, an identification profile by capturing a first image using a camera of the computing device; requesting, by the computing device, an authentication action by an authentication device; comparing, by the computing device, recognized elements of the first image and a second image, the recognized elements of the first image and the second image including at least one of ephemeral features and transient features; determining, by the computing device, whether a confidence level is above a predetermined threshold based on a comparison of the recognized elements of the first image and the second image; and completing, by the computing device, authentication of the computing device with the authentication device in response to a determination that the confidence level is above the predetermined threshold.