Privacy-Preserving Location Code Vectors for Contact Tracing
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Solution Overview
Problem
Contact tracing methods face widespread adoption challenges due to privacy concerns, particularly with technologies that record and store absolute location data, leading to limited deployment during public health crises like COVID-19.
Innovation Solution
A method and system for encrypting location data into code vectors using linear or non-linear transformations, sorting, and random modifications to obscure the data while maintaining relative relationships, ensuring that only encrypted versions are shared, making it difficult to invert and recover the original data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If absolute location data is recorded and stored on a central server for contact tracing, then contact tracing effectiveness is improved, but user privacy is compromised
Solution Approach 1:
The patent introduces code vectors as an intermediary representation of location data. Instead of storing and comparing raw GPS coordinates, the system transforms location information into code vectors through encoding and randomization processes. These code vectors serve as mediators that preserve the ability to identify proximity contacts while obscuring the actual location information, thus resolving the contradiction between contact tracing effectiveness and privacy protection
Solution Approach 2:
The system changes the parameter representation of location data from absolute coordinates to randomized code vectors. By applying random modifications and transformations to the encoded location information, the patent alters the data parameters such that the original location cannot be recovered, yet the relative proximity relationships necessary for contact tracing are maintained through distance comparison of the code vectors
2Object-affected harmful factors
If location data is encrypted into code vectors with random modifications, then data privacy is improved, but data accuracy for proximity detection may deteriorate
Solution Approach 1:
The patent applies partial randomization to the code vectors - not all aspects of the data are randomized, but only sufficient portions to achieve privacy protection. The random modifications are applied in a controlled manner that preserves the essential geometric relationships needed for proximity detection, applying just enough transformation to protect privacy while maintaining the functional accuracy required for contact tracing
3Productivity
If code vectors are compared to determine proximity, then computational efficiency is improved, but the complexity of the encoding and transformation process increases
Solution Approach 1:
The patent performs preliminary encoding and transformation of location data into code vectors before the actual contact tracing comparison operations. This preliminary action prepares the data in advance in a format optimized for efficient comparison, so that during contact tracing operations, only simple distance calculations on pre-encoded vectors are needed, rather than performing complex transformations in real-time
Data Source
AI summary
Described in detail herein is a method for encrypting or encoding time-stamped location data associated with a computing device. The method converts time and location information associated with the computing device into a vector format. The method generates a code vector based on the converted time and location vector. The method sorts entries in the code vector based at least in part on a predetermined ordering scheme. The method executes a random modification to each of the sorted entries. The method compares the code vector to at least one other code vector associated with another computing device. The method identifies other code vectors within a specified distance of the given code vector. The method concludes that the computing device and the at least one other computing device were in proximity to each other during a time period corresponding to the time information.