Abstract:
Mobile advertising using in-app ads has increased in popularity along with the substantial number of current free mobile applications in the app stores. This relatively new type of advertising has raised several concerns during the past few years. The first concern is resource consumption, such as the battery consumption that mobile advertising entails and the network traffic overhead that it consumes to download the ads. The second concern is mobile ads click fraud that threatens the mobile advertising economy. While several efforts revealed key observations regarding ads-related energy and bandwidth consumption, they did not compare these two types of consumptions among different ad networks. Unlike some previous work that just mentioned the ad networks associated with the tested apps, this thesis evaluates bandwidth and energy consumption and compares them among several popular ad networks that support ads for Android applications. The experimental procedure followed in this study demonstrated that resource consumption varies significantly among networks based on our statistical tests: For the same testing environment and duration, the bandwidth consumption in monetary value is 6.1$ for the ad network “Mobfox”, and 0.2$ for the ad network “Millennial Media”; the battery consumption in standby time is 1.3 min for the ad network “AppFlood”, and 33.2 min for the ad network “Flurry Mediation”. In addition, this study highlights a common behavior when fetching ads, where ads are fetched at the beginning of app runtime and displayed throughout the application session. From a security perspective, although most of the popular ad networks use many techniques to detect click fraud, they do not protect the client from possible collusion between publishers and ad networks. In addition, ad networks are not able to monitor the user’s activity for click fraud detection, once they are redirected to the advertising site after clicking the ad. In this thesis, we propos
Description:
Thesis. M.E. American University of Beirut. Department of Electrical and Computer Engineering, 2016. ET:6396
Advisor : Dr. Imad H. Elhajj, Associate Professor, Electrical and Computer Engineering ; Members of Committee : Dr. Ayman Kayssi, Professor, Electrical and Computer Engineering ; Dr. Ali Chehab Professor, Electrical and Computer Engineering.
Includes bibliographical references (leaves 60-68)