# Fusion of Mobile Device Signal Data Attributes Enables Multi-Protocol Entity Resolution and Enhanced Large-Scale Tracking

## TL;DR

SEXTANT is a framework that combines device attributes and spatio-temporal data to perform large-scale, multi-protocol mobile device tracking, raising privacy concerns and emphasizing the need for better standards.

## Contribution

Introduces SEXTANT, a novel framework that enhances device identification and multi-protocol entity resolution using new algorithms and data integration techniques.

## Key findings

- Effective large-scale device tracking demonstrated on simulated data
- Robust to data heterogeneity, sparsity, and noise
- Highlights privacy risks and need for new standards

## Abstract

Use of persistent identifiers in wireless communication protocols is a known privacy concern as they can be used to track the location of mobile devices. Furthermore, inherent structure in the assignment of hardware identifiers as well as upper-layer network protocol data attributes can leak additional device information. We introduce SEXTANT, a computational framework that combines improvements on previously published device identification techniques with novel spatio-temporal correlation algorithms to perform multi-protocol entity resolution, enabling large-scale tracking of mobile devices across protocol domains. Experiments using simulated data representing Las Vegas residents and visitors over a 30-day period, consisting of about 300,000 multi-protocol mobile devices generating over 200 million sensor observations, demonstrate SEXTANT's ability to perform effectively at scale while being robust to data heterogeneity, sparsity, and noise, highlighting the urgent need for the adoption of new standards to protect the privacy of mobile device users.