Weighted Authentication Value for Seamless Device Access
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Solution Overview
Problem
Current electronic devices require cumbersome security procedures such as PIN entry or biometric readings for access, which users find inconvenient, and existing solutions do not effectively utilize available data like swipe patterns, location, and connected devices for secure authentication.
Innovation Solution
An electronic device system that determines an authentication value based on weighted confidence indicators from various authentication components, such as Bluetooth, WiFi, location, and biometric data, allowing for secure access without traditional security challenges when authorized user patterns are recognized.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security procedures (PIN entry, biometric reading) are implemented, then security is improved, but ease of operation deteriorates
Solution Approach 1:
The system performs preliminary learning of user patterns (swipe patterns, grip characteristics, device usage timing, connected devices) during normal operation without requiring explicit user input. This pre-collected data is then used during authentication to determine whether security challenges are necessary, eliminating the need for traditional PIN or biometric entry when patterns match authorized users.
Solution Approach 2:
The authentication system serves itself by automatically analyzing device data and usage patterns to determine authentication outcomes. The electronic device monitors its own usage characteristics and makes authentication decisions without requiring external security inputs from users, thereby maintaining security while improving ease of operation.
2Reliability
If multiple authentication components are integrated, then reliability is improved, but device complexity increases
Solution Approach 1:
The system merges multiple authentication components (swipe pattern analysis, grip characteristics, device usage timing, connected device detection, location data) into a unified authentication framework. These diverse data sources are combined and evaluated together to produce a single authentication decision, improving reliability while managing complexity through integration rather than separate systems.
Solution Approach 2:
The authentication system serves multiple functions: it collects data during normal operation, learns user patterns over time, performs real-time authentication analysis, and makes security decisions. This multi-functional approach consolidates what could be separate systems into a single universal authentication mechanism.
Data Source
AI summary
A method on an electronic device for a wireless network is described. A plurality of component confidence indicators is determined for a corresponding plurality of authentication components of the electronic device. The plurality of component confidence indicators is grouped into at least first and second sets. A first set confidence indicator is determined based on the component confidence indicators of the first set. A second set confidence indicator is determined based on the component confidence indicators of the second set. An authentication value is determined based on the first set confidence indicator, weighted by a first authentication factor for the first set, and the second set confidence indicator, weighted by the first authentication factor. The electronic device is unlocked based on the authentication value.