Activity Confirmation Engine Using Cryptographic Object Derivation
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Solution Overview
Problem
Users engage in physical activities that they want to verify and rate for health insurance benefits or other purposes, but they are concerned about sharing their personal data with third parties, necessitating a method to confirm and rate activities without revealing raw sensor data.
Innovation Solution
A computing device processes sensor data locally using an app to create a representation of the activity that can be verified by third parties without exposing the underlying data, using cryptographic objects and engines like Key Generating Engine (KGE), Proof Generating Engine (PGE), and Proof Verifying Engine (PVE) to ensure authenticity and privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data is shared with third parties for activity verification, then activity confirmation reliability is improved, but user data privacy is compromised
Solution Approach 1:
The patent extracts only the essential verification information from the complete sensor dataset. The confirmation engine derives activity confirmation results that contain sufficient information for third-party verification while deliberately excluding the raw sensor data that would compromise user privacy. This selective extraction resolves the contradiction by providing what is needed for reliability without what would harm privacy.
Solution Approach 2:
The patent introduces a confirmation engine as an intermediary between the sensor data collection system and third-party verification systems. This intermediary processes the raw sensor data locally, generates verified activity confirmations, and shares only these processed results with third parties. The intermediary layer ensures that third parties can verify activities reliably while users maintain control over their raw data and privacy.
2Loss of information
If cryptographic processing is applied to protect user data, then user privacy is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service cryptography where the user's computing device performs all cryptographic operations locally without requiring external cryptographic services. The confirmation engine uses cryptographic functions to protect user data and verify activities, but the cryptographic processing is embedded within the device itself, reducing the need for complex external infrastructure and making the system more self-sufficient.
Solution Approach 2:
The patent segments the cryptographic functionality into distinct components within the confirmation engine. Rather than implementing a monolithic cryptographic system, the patent divides cryptographic operations into separate modules that handle different aspects of data protection and verification. This segmentation makes the cryptographic system more manageable and easier to implement while maintaining strong privacy protection.
3Loss of information
If activity data is processed locally on user device, then user data privacy is improved, but processing capability requirements increase
Solution Approach 1:
The patent applies partial processing by performing only the essential cryptographic and confirmation operations locally on the user device, rather than processing all possible data or using excessive computational resources. The confirmation engine focuses on deriving activity confirmations and protecting privacy-critical data, while leaving other processing requirements moderate and manageable for typical mobile devices.
Data Source
AI summary
A method allows third party authentication of confirmation of an activity performed by a user of a computing device that receives first and second datasets of values for a plurality of attributes respectively obtained from a plurality of sensors associated with the computing device. The first and second datasets reflect a user activity obtained over first and second periods of time, respectively, during which the activity occurs. The computing device compares a subset of the attribute values in the first dataset to their corresponding attribute values in the second dataset to confirm whether they match to within a prescribed degree. If the matching is confirmed, a representation is created of an indicia of the confirmation and a set of cryptographic objects is derived from the representation such that a third party is able to authenticate the confirmation without being able to derive the first or second datasets.