Mobile dynamic content distribution networks
MSWiM '04 Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
A first look at traffic on smartphones
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
A first look at mobile hand-held device traffic
PAM'10 Proceedings of the 11th international conference on Passive and active measurement
Identifying diverse usage behaviors of smartphone apps
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Don't kill my ads!: balancing privacy in an ad-supported mobile application market
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
Unsafe exposure analysis of mobile in-app advertisements
Proceedings of the fifth ACM conference on Security and Privacy in Wireless and Mobile Networks
ProfileDroid: multi-layer profiling of android applications
Proceedings of the 18th annual international conference on Mobile computing and networking
Breaking for commercials: characterizing mobile advertising
Proceedings of the 2012 ACM conference on Internet measurement conference
AdDroid: privilege separation for applications and advertisers in Android
Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security
Rise of the planet of the apps: a systematic study of the mobile app ecosystem
Proceedings of the 2013 conference on Internet measurement conference
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Recent years have seen an explosive growth in the number of mobile devices such as smart phones and tablets. This has resulted in a growing need of the operators to understand the usage patterns of the mobile apps used on these devices. Previous studies in this area have relied on volunteers using instrumented devices or using fields in the HTTP traffic such as User-Agent to identify the apps in network traces. However, the results of the former approach are difficult to be extrapolated to real-world scenario while the latter approach is not applicable to platforms like Android where developers generally use generic strings, that can not be used to identify the apps, in the User-Agent field. In this paper, we present a novel way of identifying Android apps in network traces using mobile in-app advertisements. Our preliminary experiments with real world traces show that this technique is promising for large scale mobile app usage pattern studies. We also present an analysis of the official Android market place from an advertising perspective.