Crowdsourced Privacy Rating System for Application Trust
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Solution Overview
Problem
Users lack reliable sources for privacy-related information about applications, making it difficult to determine the trustworthiness of applications and their handling of personal data, as existing centralized certification mechanisms are not foolproof and crowdsourced ratings are often unreliable and burdensome.
Innovation Solution
A system that automatically collects application use information from devices to compute privacy ratings in a crowdsourced fashion, presenting them in a quantifiable and understandable form, customizable for specific devices and environments, and capable of evolving over time based on continuous data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized certification mechanisms are used to provide privacy information, then users can obtain privacy-related information about applications, but the certification is not foolproof and users still lack reliable privacy information
Solution Approach 1:
The patent introduces a crowdsourced rating system as an intermediary between users and applications. Multiple users contribute privacy observations and experiences, which are aggregated into composite ratings. This crowdsourced intermediary provides more reliable privacy information than centralized certification alone, as it reflects real-world usage patterns from multiple independent sources.
Solution Approach 2:
The patent combines centralized certification mechanisms with crowdsourced user ratings into a unified privacy information system. The composite privacy ratings merge expert certification data with aggregated user experiences, creating a more comprehensive and reliable privacy assessment that leverages both top-down certification and bottom-up user feedback.
2Reliability
If crowdsourced ratings are implemented to provide privacy information, then users can access privacy-related information, but the process becomes burdensome for users
Solution Approach 1:
The system enables users to passively contribute to privacy ratings through automated data collection from their device usage patterns. Users do not need to manually complete surveys or provide detailed feedback; instead, the system automatically monitors application behavior, data access patterns, and privacy-related events to generate crowd-sourced ratings, significantly reducing user burden while maintaining data accuracy.
Solution Approach 2:
The patent implements automated feedback loops where user privacy experiences are continuously collected, processed, and reflected in updated privacy ratings. The system provides feedback to users about privacy risks and application behaviors based on aggregated crowd data, enabling users to make informed decisions without bearing the burden of manual rating generation.
3Measurement precision
If automated data collection is performed to generate privacy ratings, then accurate and unbiased ratings can be produced, but the system complexity increases
Solution Approach 1:
The patent segments the privacy rating system into distinct functional modules: automated data collection components that monitor application behavior, processing components that aggregate and analyze usage patterns, and output components that generate and display privacy ratings. This segmentation allows each module to specialize in specific tasks, improving measurement precision while managing system complexity through modular architecture.
Solution Approach 2:
The patent creates a multi-functional automated data collection system that simultaneously performs multiple tasks: monitoring data access patterns, tracking application behavior, analyzing privacy policy compliance, and generating crowd-sourced ratings. This universal system handles diverse privacy assessment requirements through a single integrated platform, reducing overall system complexity compared to separate specialized systems.
Data Source
AI summary
An approach is provided for generating privacy ratings for applications. A privacy ratings platform determines use information associated with one or more applications executing on one or more devices. By way of example, the use information is determined based, at least in part, on usage data associated with one or more input sources, one or more components, one or more categories of personal information, or a combination thereof associated with the one or more devices. The privacy ratings platform then processes and/or facilitates a processing of the use information to determine one or more privacy ratings for the one or more applications.