Mobile App Privacy Sandboxing via Isolated Execution Profiles
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Solution Overview
Problem
The current smartphone ecosystem lacks effective mechanisms to prevent curious parties from covertly linking and aggregating user data across different mobile applications without consent, leading to unregulated data aggregation by mobile apps, advertising agencies, and network sniffers, compromising user privacy.
Innovation Solution
The MASK framework introduces private execution modes (identifiable, pseudonymous, and anonymous) that allow users to manage app usage linkability based on their needs, creating isolated runtime environments to prevent unauthorized data correlation by intercepting identifying information and redirecting file system operations, ensuring only functionally dependent app usages are linkable while keeping others unlinkable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If device identifiers and persistent storage are used to maintain app usage consistency, then app functionality and user experience are improved, but user privacy and data unlinkability deteriorate
Solution Approach 1:
The patent segments the execution environment into isolated sandboxes for each app, with separate persistent storage spaces. This allows each app to maintain its own state and usage data independently, preventing cross-app correlation while maintaining individual app functionality. The segmentation of storage and execution contexts enables users to have consistent experiences within apps without creating aggregate profiles across apps.
Solution Approach 2:
The patent introduces an intermediary layer (the privacy manager and sandboxing mechanism) between the app and the device's identifying information. This intermediary intercepts and isolates device identifiers and persistent storage access, allowing apps to function normally while preventing direct access to identifying information that would enable cross-app tracking.
2Productivity
If advertising agencies and network sniffers can access app usage data, then targeted advertising and network functionality are improved, but user privacy and control over data aggregation deteriorate
Solution Approach 1:
The patent extracts identifying information and persistent storage access from the app execution context and places them in isolated sandbox environments. This extraction prevents advertising agencies and network sniffers from accessing usage data across different apps, while still allowing individual apps to collect data for their specific purposes. The useful advertising functionality within apps is preserved, but the harmful cross-app aggregation is removed.
3Stability of the object's composition
If consistent device identifiers are used across apps, then app linkage and service continuity are improved, but susceptibility to surveillance and data aggregation deteriorates
Solution Approach 1:
The patent applies local quality by providing consistent device identifiers and persistent storage only within the local sandbox context of each individual app, while preventing these identifiers from being accessible to other apps or external observers. Each app experiences stable, consistent identification for its own purposes, but this consistency does not extend beyond the app's isolated execution environment, thereby preventing surveillance and cross-app aggregation.
Data Source
AI summary
A technique is presented for controlling behavior tracking by mobile apps executing on a mobile computing device. A set of profiles are managed by a privacy manager, where each profile represents a different isolated execution environment on the mobile computing device and defines a set of privacy rules governing an application while executing in an associated execution environment. Prior to launching the app, a user of the app is prompted by the privacy manager to select a profile for the app from the set of profiles. The privacy manager in turn applies the set of privacy rules associated with the selected profile to the app during execution of the app on the mobile computing device.