Trusted Wearable Services Sandboxing for Private Sensor Processing
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Solution Overview
Problem
Existing split-compute architectures in wearable devices fail to maintain privacy of sensor data from companion devices, as sandboxes do not recognize and protect data from wearable devices effectively.
Innovation Solution
Introduce a trusted wearable services module on the companion device with a secure connection to wearable sensors, encrypting and decrypting data to determine user context without sharing sensitive information with other modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If sensor data is processed on a companion device to determine user context, then processing power and battery life of the wearable device are improved, but privacy of sensor data is compromised due to lack of sandbox protection
Solution Approach 1:
The system segments the companion device into two distinct environments: a sandboxed environment that receives and processes encrypted sensor data from the wearable device, and a non-sandboxed environment for other applications. This segmentation ensures that sensitive sensor data remains isolated and protected while still enabling context determination processing on the companion device, thus preserving battery life without compromising privacy.
Solution Approach 2:
The patent introduces an intermediary mechanism in the form of encrypted data transmission and a dedicated sandboxed processing environment. The encrypted sensor data acts as an intermediary that allows the companion device to process information without exposing the actual sensitive content to non-sandboxed applications, thereby enabling energy-efficient processing while maintaining privacy protection.
2Object-affected harmful factors
If sandboxing is implemented to protect sensor data privacy, then data security is improved, but system complexity increases due to isolated module architecture
Solution Approach 1:
The sandboxed environment on the companion device is designed to be universal and multi-functional. It can handle various types of sensor data from different wearable devices and support multiple processing operations (context determination, analytics, etc.) within a single isolated module. This approach maintains data security while avoiding the need for separate isolated modules for each function, thereby reducing overall system complexity.
Data Source
AI summary
Techniques include adding a trusted wearable services module to a sandbox/isolated module on the companion device. e.g., to Private Compute Core. This trusted wearable services module has a secure connection to the camera on the wearable device and prevents other modules on the companion device from viewing the private data. The trusted wearable services has the ability to encrypt and decrypt data from the camera and also performs the processing used to determine user context in an ambient sensing situation.


