IoT Privacy Assistant for Managing User-Specific Permission Overload
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Solution Overview
Problem
Users face an overwhelming number of permission decisions for sensitive data and functionality access across various technologies, with existing permission-based mechanisms failing to accurately reflect individual privacy preferences due to diverse user preferences and lack of awareness.
Innovation Solution
A personalized privacy assistant system that utilizes machine learning and statistical analysis to create user-specific privacy preference models, recommending and configuring permission settings for applications and IoT resources based on collected user data and behavior, with optional local or cloud-based storage and communication with data centers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If permission-based mechanisms are provided for each application and device, then users can control access to sensitive data and functionality, but the number of permission decisions becomes overwhelming and difficult to manage
Solution Approach 1:
The patent segments the large number of permission decisions into manageable groups by creating a digital twin representation that aggregates permissions across multiple applications and devices. This allows users to manage privacy settings at a higher level of abstraction rather than individually for each app-device combination.
Solution Approach 2:
The patent introduces a digital twin as an intermediary layer between the user and the actual permission mechanisms. This digital twin acts as a mediator that translates complex permission decisions into simplified representations, reducing the cognitive burden on users while maintaining granular control capabilities.
2Measurement precision
If users are provided with detailed permission settings for each technology, then they can make informed decisions about data access, but most users are unaware of or uncomfortable with many permissions they have consented to
Solution Approach 1:
The patent performs preliminary analysis and aggregation of permission data before presenting it to users. By pre-processing the complex permission information into a digital twin representation, the system prepares the data in an easily understandable format, allowing users to make informed decisions without being overwhelmed by raw permission details.
Solution Approach 2:
The patent creates a digital copy (digital twin) of the user's permission landscape that mirrors the actual permissions across applications and devices. This copy allows users to review and manage their privacy settings in a simplified interface without directly interacting with the complex underlying permission structures.
3Ease of operation
If one-size-fits-all privacy settings are implemented, then configuration is simplified, but diverse user preferences cannot be accurately captured
Solution Approach 1:
The patent implements dynamic permission management through the digital twin, which can adapt to individual user preferences while maintaining simplified configuration. The system allows users to define their privacy preferences once, and the digital twin dynamically applies these preferences across multiple applications and devices, accommodating diverse preferences without requiring complex per-app configuration.
Data Source
AI summary
An Internet of Things (IoT) resource remotely senses data about a user. A computing device of the user comprises a personal privacy app (“PPA”) that: receives data about the IoT resource, wherein the data about the IoT resource comprises available user-specific privacy requests related to data practices of the IoT resource; communicates a privacy request for the user with respect to the IoT resource, wherein the privacy request is one of the available user-specific privacy requests and wherein the privacy request communicated by the PPA is based on the data received about the IoT resource; and in response to a query related to the privacy request, causes electronic documentation to be transmitted that demonstrates that the user qualifies to submit the privacy request, such that the privacy request is applied to data collected about the user by the IoT resource.