Personalized Privacy Assistant for IoT Permission Automation

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Solution Overview

Problem

Users face an overwhelming burden in managing numerous permission settings for apps and IoT resources, leading to inaccurate reflection of their privacy preferences due to lack of awareness and comfort with these settings.

Innovation Solution

A personalized privacy assistant system that utilizes machine learning and statistical analysis to generate user-specific privacy preference models, helping users configure permission settings for apps and IoT resources based on their individual comfort levels and preferences.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If permission-based mechanisms are provided to control access to sensitive data and functionality, then user control over privacy is improved, but the number of permission decisions users must make increases to over one hundred

Engineering Contradiction:

Improveuser control over privacyVSAvoidnumber of permission decisions

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The patent introduces a privacy assistant as an intermediary system that automatically manages permission decisions on behalf of users. The privacy assistant analyzes app requests, evaluates them against user privacy preferences, and makes automated permission decisions, thereby reducing the burden of over one hundred manual permission decisions while maintaining user control through preference-based automation

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The privacy assistant enables users to define their privacy preferences once, and the system then autonomously makes permission decisions based on these preferences. This self-service mechanism allows the system to automatically handle subsequent permission requests without requiring users to manually review each of the over one hundred permission decisions

Inventive Principle:

Principle #25Self-service

2Reliability

If users are expected to make numerous permission decisions, then comprehensive privacy control is improved, but user awareness and comfort with the permissions decreases

Engineering Contradiction:

Improveprivacy control accuracyVSAvoiduser awareness and comfort

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The privacy assistant acts as an intermediary between users and the complex permission landscape, translating user preferences into informed permission decisions. It provides users with awareness of what permissions are being requested and why, while maintaining comfort by handling the cognitive burden of evaluating over one hundred permission decisions

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements feedback mechanisms where the privacy assistant communicates permission decisions and their rationale to users. This feedback loop enhances user awareness by explaining permission requests in context while maintaining comfort through transparent, preference-based automated decisions that align with user values

Inventive Principle:

Principle #23Feedback

3Ease of operation

If one-size-fits-all privacy settings are implemented, then ease of configuration is improved, but accuracy in capturing diverse user privacy preferences deteriorates

Engineering Contradiction:

Improveease of configurationVSAvoidprivacy preferences accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent implements local quality by allowing users to define specific privacy preferences for different contexts, app categories, or types of data access. Rather than a single global setting, the system enables nuanced, localized privacy controls that can vary by situation, thereby accurately capturing diverse user preferences while maintaining ease of configuration through structured preference templates

Inventive Principle:

Principle #3Local quality

4Adaptability or versatility

If the number of privacy settings increases to cover diverse technologies and environments, then adaptability to different conditions is improved, but the number of settings becomes unrealistically large for people to manage

Engineering Contradiction:

Improvecoverage of technologies and environmentsVSAvoidnumber of settings to manage

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The privacy assistant implements universality by providing a single, unified interface and set of preference definitions that automatically apply across multiple technologies and environments including mobile apps, web browsers, and IoT devices. This multi-functional approach allows one privacy assistant to manage permissions across diverse platforms without requiring separate settings for each technology

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system segments privacy management into organized categories and contexts, grouping related permissions and settings into manageable units. By segmenting the overwhelming number of settings into structured, contextualized groups, the system makes the diverse range of privacy controls across multiple technologies manageable while maintaining comprehensive adaptability

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS12235973B2Personalized privacy assistant

Publication Date: 2025.02.25 CARNEGIE MELLON UNIV

AI summary

A system comprises a IoT resource and a computing device of a user. The computing device comprises a processor that executes a personal privacy app that receives data about the IoT resource and communicates a preference setting for the user with respect to the IoT device. The preference setting is based on the data received about the IoT resource.