Multi-Factor Trust Score for Medical Data Reliability
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Solution Overview
Problem
In the medical technology field, there is a significant variance in the trustworthiness of data from different sources due to factors like device type, data path, and validation level, posing risks if incorrect information is acted upon.
Innovation Solution
A multi-factor trust score system is implemented, using metrics such as device attestation, gateway attestation, identity attestation, attribution, consent/approval, device security level, and gateway security level, with weights assigned to each metric to determine a weighted trust score, enabling appropriate actions based on data provenance and trust levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is collected from multiple sources with different validation levels, then data completeness is improved, but data reliability deteriorates due to variance in trustworthiness
Solution Approach 1:
The system changes the parameter of data evaluation by introducing a trust score that quantifies the reliability of data from different sources. Instead of treating all data equally, the system assigns different trust scores based on source characteristics (device type, validation level, data path), allowing the system to weigh data reliability against completeness by adjusting which sources are prioritized based on their trust scores.
Solution Approach 2:
The system applies local quality by evaluating and scoring different data sources individually based on their specific characteristics. Each data source (device, gateway, validation level) is assessed on its own merits and assigned a trust score that reflects its local quality and reliability, rather than applying a uniform standard to all data sources.
2Reliability
If trust score evaluation considers multiple metrics (device attestation, gateway attestation, identity attestation), then data reliability is improved, but system complexity increases
Solution Approach 1:
The system segments the trust score evaluation into distinct metrics and components: device attestation, gateway attestation, identity attestation, and other factors. Each metric is evaluated separately and then combined to produce the overall trust score. This segmentation makes the complex evaluation process more manageable and modular, allowing each component to be optimized independently.
Solution Approach 2:
The trust score system serves multiple functions simultaneously: it evaluates device security, validates data paths, confirms identity authentication, and determines overall data reliability. By consolidating these multiple evaluation functions into a single trust score mechanism, the system reduces operational complexity while maintaining comprehensive reliability assessment.
3Reliability
If weighted trust score is calculated using multiple metrics with weights, then action confidence is improved, but computational requirements increase
Solution Approach 1:
The system changes the computational approach by using weighted scoring where pre-determined weights are applied to standardized metric values. Rather than performing complex real-time analysis, the system uses established weightings (e.g., device attestation weight, gateway attestation weight) that can be pre-calculated and stored, reducing computational burden while maintaining high action confidence through the weighted aggregation of trusted metrics.
Data Source
AI summary
Various implementations described herein are directed to determining a multi-factor trust score. Data from one or more endpoint devices is received over a gateway. A trust score is determined based on a plurality of metrics. The plurality of metrics including at least: a first attestation process performed for the one or more endpoint devices, and a second attestation process performed for the gateway. The trust score is sent to an analytics server. The trust score is configured to be used by the analytics server to determine an alert and/or a command based on the trust score.