Identifying diverse usage behaviors of smartphone apps

By Qiang Xu, Jeffrey Erman, Alexandre Gerber, Z. Morley Mao, Jeffrey Pang, Shobha Venkataraman. ACM/SIGCOMM Internet Measurement Conference, 2011

465 citations recorded by the source corpus.

Smartphone users are increasingly shifting to using apps as "gateways" to Internet services rather than traditional web browsers. App marketplaces for iOS, Android, and Windows Phone platforms have made it attractive for developers to deploy apps and easy for users to discover and start using many network-enabled apps quickly. For example, it was recently reported that the iOS AppStore has more than 350K apps and more than 10 billion downloads. Furthermore, the appearance of tablets and mobile devices with other form factors, which also use these marketplaces, has increased the diversity in apps and their user population. Despite the increasing importance of apps as gateways to network services, we have a much sparser understanding of how, where, and when they are used compared to traditional web services, particularly at scale. This paper takes a first step in addressing this knowledge gap by presenting results on app usage at a national level using anonymized network measurements from a tier-1 cellular carrier in the U.S. We identify traffic from distinct marketplace apps based on HTTP signatures and present aggregate results on their spatial and temporal prevalence, locality, and correlation.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/b93f411d022b4cce38763c3c8470dcd2e7acf5c7

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In Computer Networks and Communications

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Citations in the corpus

You Are Who You Know and How You Behave: Attribute Inference Attacks via Users' Social Friends and Behaviors (2016, background): “Likewise, previous measurement study [43] found that some apps are only popular in certain cities, implying the possibility of inferring cities a user lived in using the apps the user used or liked.”
An in-depth study of LTE: effect of network protocol and application behavior on performance (2013, background): “HTTP dominates the application-layer protocol usage on mobile devices [34].”
A first look at cellular machine-to-machine traffic: large scale measurement and characterization (2012, result): “In contrast to their study, we find that most M2M applications use custom protocols that are not identifiable using the traffic classification technique used in [24].”
Attribute Inference Attacks in Online Social Networks (2018, background): “Likewise, a previous measurement study [61] found that some apps are only popular in certain cities, implying the possibility of inferring cities a user lived in using the list of apps the user used or liked.”