Who do you sync you are? Smartphone Fingerprinting based on Application Behaviour
by Tim Stöber, Mario Frank, Ivan Martinovic and Jens Schmitt

The overall network traffic patterns generated by today's smartphones result
from the typically large and diverse set of installed applications. In addition
to the traffic generated by the user, most applications generate characteristic
traffic from their background activities, such as periodic update requests or
server synchronisation. Although the encryption of transmitted data in 3G
networks prevents an eavesdropper from analysing the content,  periodic traffic
patterns leak side-channel information like timing and %the amount of transmitted 
data volume. In this work, we extract such side-channel features from network
traffic generated from the most popular applications, such as Facebook, WhatsApp,
Skype, Dropbox, and others, and evaluate whether they can be used to reliably
identify a smartphone. By computing fingerprints from 6 hours of background
traffic, we show that 15 minutes of monitored traffic suffice to reliably 
identify a smartphone based on its behavioural fingerprint with a success 
probability of 90\%.