Wearable Authentication via Cross-Device Sensor Correlation
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Solution Overview
Problem
Wearable devices with limited user interfaces, such as smart rings, face challenges in authentication and security due to their inability to connect or disconnect from networks and services explicitly, leading to potential security vulnerabilities if lost or stolen.
Innovation Solution
An apparatus and method that utilize sensor correlation data to authenticate wearable devices. This involves receiving authentication requests, identifying sensor sets, generating correlation data, selecting correlated sensors, and authenticating devices based on correlated sensor data, allowing for secure network access without explicit user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wearable devices authenticate based on explicit user input through user interfaces, then authentication security is improved, but device complexity and user interaction requirements increase
Solution Approach 1:
The wearable device performs authentication automatically using its own sensors to detect biometric signals and determine user presence without requiring explicit user input through a user interface. The device self-authenticates by analyzing sensor data patterns that indicate the user is wearing or near the device.
2Reliability
If wearable devices use biometric signals for authentication, then authentication security is improved, but compatibility between devices from different manufacturers deteriorates
Solution Approach 1:
The authentication system uses multiple different sensor types (accelerometer, gyroscope, magnetometer, barometer, microphone, camera) that can detect various biometric signals. This multi-sensor approach ensures compatibility across devices from different manufacturers while maintaining security through diverse biometric measurement capabilities.
3Measurement precision
If wearable devices collect and analyze biometric data for authentication, then authentication accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system analyzes multiple sensor data patterns simultaneously (acceleration, rotation, magnetic field, pressure, audio, visual) to authenticate the user. By performing multiple partial analyses in parallel rather than sequential, the system achieves high authentication accuracy while minimizing processing time.
Data Source
AI summary
Apparatus comprising means for: receiving a request to authenticate a first device; obtaining information identifying a first set of sensors associated with the first device; obtaining information identifying a second set of sensors associated with a second device; obtaining correlation data indicating correlations between sensors in the first set of sensors and sensors in the second set of sensors; selecting a first sensor from the first set of sensors and a second sensor from the second set of sensors based on the correlation data; and authenticating the first device in response to determining that data from the first sensor is correlated with data from the second sensor.