DECODE: Detecting Co-Moving Wireless Devices Detecting Co-Moving Wireless Devices Gayathri Chandrasekaran, Mesut Ali Ergin, Marco Gruteser, Rich Martin (WINLAB, Rutgers University)

DECODE: Detecting Co-Moving Wireless Devices

Gayathri Chandrasekaran, Mesut Ali Ergin, Marco Gruteser, Rich Martin

(WINLAB, Rutgers University)

Jie Yang and Yingying Chen(Department of ECE, Stevens Institute of Technology)

Co-Movement

Moving Together in Close Proximity – (~ Few Meters)

Movement of – Multiple Transmitters held by the same person– Multiple Radios attached on the same device.

Motivation

GSM <SIM ID>Wifi <MAC Address> Bluetooth <Bluetooth ID>

How to map different Transmitters to a Device or Person ?

- Friend Finder Application

Motivation: Social Network MiningDynamic Human Social Network.

Viral Marketing(use pre-existing social networks to produce increases in brand awareness)

Localize and Estimate ?

(X1,Y1)

Localize and Estimate ?

Co- Mobile:Euclidean Distance <

Threshold

TRIVIAL ?

Localize and Estimate ?

Position Estimates Are Not Stable

Co-Mobile Transmitters

Approach

Detect Co-Movement by Observing RSSI– Co-Moving transmitters have Correlated fades– Dynamics of the environment are captured

Metric: Correlation Coefficient.

Properties of Co-Mobile Transmitters

Mobile: Small Scale Fading & Shadow FadingDifferent Small Scale FadingSimilar Shadow Fading

Non-

Co-Mobile Transmitters

Different Small Scale And Large Scale Fading

Correlation Co-Efficient

Pearson’s Product Moment Correlation Coefficient:-Determines the Linear Relationship between two Random Variables (Observed RSSI from 2 Devices)

Ranges between [-1, +1]+1 - Strong Positive Correlation0 - No Correlation-1 - Strong Negative Correlation

Experiment Goals

1. Quantify Co-Movement detection rates1. Within Same Technology2. Across Different Radio Technology

2. Quantify the Effect of Speed on the time taken to detect co-movement

Experimental Setup

5

Detecting Co-Movement (Similar Radio -

Wifi)

Impact of Speed on Co-Movement Detection Time

Threshold = 0.6

Conclusion: 50-100 Sec of Observation Required.

Impact of Speed on Co-Movement Detection Time

Other Observations

Sampling rates have a little effectWorks with mixed radio technologies (in 2.4GHz band) motes, wifiCorrelation Co-Efficient Threshold = 0.6 yields High Detection Rates and Low False PositivesDetect Mobile Periods by Observing Variance(>3) of RSSI over time.

Note: It only needs a single measurement node (base station)

Conclusion and Future WorkSimple and effective technique to Detecting Co-Mobile transmitters through signal strength analysis ( 2 minutes of Observation )Can work with just 1 receiver when the Localization infrastructure is Not in place

Future Work - Would a similar technique work outdoors using cellular signal strength information to detect co-moving cell phones?

QUESTIONS?

Thanks !

Determining Threshold (Τ)

Detecting Co-Movement (Different Radios)

Co-mobile Mote and Wifi

Mobility Detection using Variance.

Impact of Sampling Rate in Co-Movement Detection Time

DECODE System Design

Summary

Simple and effective technique to Detecting Co-Mobile transmitters through signal strength analysis ( 2 minutes of Observation )Can work with just 1 receiver when the Localization infrastructure is Not in placeCan Work Across radio TechnologiesLesser Time with increased Speed.Insensitive to Sampling Frequency.

Future Work

Would a similar technique work outdoors using cellular signal strength information to detect co-moving cell phones?

Application in Mind: Optimize phone Battery life by turning off the GPS for one of the Co-Mobile Devices.

How to Extend this to Detect Static Co-Located Transmitters?