Third Eye: Inferring the State of Your Smartphone Through Wi-Fi

Wi-Fi is one of the most notable and prevalent wireless technologies today. Smartphones and other Wi-Fi-enabled devices find nearby networks using management frames known as probe-requests. In this paper, we infer the state of smartphones by passively monitoring their transmitted probe-requests. We leverage the differential behaviour of probe-request bursts and their content, based on their device states such as active/static screen and Wi-Fi/power-saving mode ON/OFF. We use a Random Forest based approach that can successfully predict smartphone states just leveraging individual bursts. Based on an evaluation using a real-world dataset of more than 200 smartphones (having a variety of operating systems), with ground truth data available, we show that our model reliably predicts states with accuracy ≥ 98%.

Authors

Institutions

Publication Details

Published
2024-09-09
DOI
https://doi.org/10.1109/lcn60385.2024.10639774
Primary Topic
Bluetooth and Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Third Eye: Inferring the State of Your Smartphone Through Wi-Fi

Mathieu Cunche, Abhishek Mishra
Bluetooth and Wireless Communication Technologies
article

Third Eye: Inferring the State of Your Smartphone Through Wi-Fi

Mathieu Cunche, Abhishek Mishra
article en

Abstract

Wi-Fi is one of the most notable and prevalent wireless technologies today. Smartphones and other Wi-Fi-enabled devices find nearby networks using management frames known as probe-requests. In this paper, we infer the state of smartphones by passively monitoring their transmitted probe-requests. We leverage the differential behaviour of probe-request bursts and their content, based on their device states such as active/static screen and Wi-Fi/power-saving mode ON/OFF. We use a Random Forest based approach that can successfully predict smartphone states just leveraging individual bursts. Based on an evaluation using a real-world dataset of more than 200 smartphones (having a variety of operating systems), with ground truth data available, we show that our model reliably predicts states with accuracy ≥ 98%.

Université Claude Bernard Lyon 1 (FR), Institut National des Sciences Appliquées de Lyon (FR)
Affordable and clean energy
Openalex Percentile: Top 90%
Bluetooth and Wireless Communication Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Third Eye: Inferring the State of Your Smartphone Through Wi-Fi — Mathieu Cunche, Abhishek Mishra · (2024) | TGRS Research Map | TGRS