Artificial Contextual Data Generation for Privacy Protection
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Solution Overview
Problem
The collection and analysis of contextual data for ubiquitous computing pose significant privacy concerns, as sensitive information can be inferred from location data, leading to potential attacks and breaches, and existing methods like data perturbation or security architectures are inadequate in protecting user privacy without compromising data utility.
Innovation Solution
A system generates artificial contextual data based on real user data, grouping it into personas to obscure the real data, making it difficult for third parties to distinguish without explicit authorization, using historical data and noise addition to ensure realism and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If data perturbation is used to protect user privacy, then privacy protection is improved, but data utility deteriorates due to imprecision
Solution Approach 1:
The patent generates artificial contextual data that copies the statistical properties and patterns of real contextual data without replicating actual user information. The artificial data mimics the distribution, relationships, and features of real data while being completely fabricated, thereby providing privacy protection while maintaining data utility for analysis and service improvement.
Solution Approach 2:
The patent transforms real contextual data into artificial contextual data by changing the fundamental nature of the data from actual measurements to synthetic constructions. The artificial data preserves statistical parameters and patterns but changes the semantic content, allowing privacy protection without sacrificing the ability to perform contextual analysis and improve services.
2Reliability
If security architectures are used to limit data access, then security is improved, but privacy protection is insufficient due to potential breaches
Solution Approach 1:
The patent introduces artificial contextual data as an intermediary between real user data and external systems. Instead of directly storing and transmitting real contextual data, the system uses artificial data that mirrors the structure and patterns of real data while containing no actual user information, thereby providing both security through data minimization and privacy protection through data fabrication.
Solution Approach 2:
The patent creates copies of real contextual data in the form of artificial data that replicate statistical properties and patterns. These copies can be freely shared and processed without exposing actual user information, providing a layer of privacy protection that complements security architectures by addressing the root cause of privacy breaches rather than just securing the data storage.
3Object-affected harmful factors
If location data is modified to preserve privacy, then privacy protection is improved, but location accuracy deteriorates
Solution Approach 1:
The patent generates artificial location data that copies the statistical properties, movement patterns, and spatial distributions of real location data without replicating actual coordinates or trajectories. The artificial location data maintains the same statistical characteristics and patterns while being completely fabricated, thereby providing privacy protection while preserving location accuracy for service purposes.
Data Source
AI summary
Embodiments of the present disclosure provide a method and system for protecting privacy by generating artificial contextual data. The system collects real contextual data related to a user. The system then generates artificial contextual data, based on the collected real contextual data. The system also groups the generated contextual data into one or more groups. Each group of contextual data corresponds to a persona that can be presented as the user's persona. Subsequently, the system transmits the generated contextual data to an entity, thereby allowing the user to obscure the real contextual data related to the user.