Abstract
In recent years, the smart phone application market has expanded rapidly. One of reasons is the popularity of free applications. A developer acquires his revenues by including advertising libraries in his own application. However, some problems about these advertising libraries become clear from recent researches. Especially in the leakage of privacy information is known as a typical problem which advertising libraries cause. In order to solve this problem, the technology which detects advertisement libraries is important. In this paper, we propose a method for detection of Android ad library. We focus on the acquisition and redraw of advertising image operation which are the basic operations of mobile advertisement. Firstly, we tried running some applications with advertisements. Then, It turned out that mobile advertisements acquire advertising images from server and set that image on the screen at a fixed interval. By modifying AndroidOS, logging HTTP connections and View object redraw behaviors, we confirmed the ad image acquisition behavior. Moreover, to take advantage of the periodicity of this behavior, we carried out Fourier-transform the invocation time data of HTTP connections and redraw of View objects. Then, we extracted the periodicity by calculating correlation coefficient for these two data. From the value of correlation coefficient, it is possible to judge whether advertisement library is incorporated into an application or not. As a result, our proposal method results in a output of about 76 % detection rate.
| Original language | English |
|---|---|
| Title of host publication | 2015 International Conference on Information Networking, ICOIN 2015 |
| Publisher | IEEE Computer Society |
| Pages | 104-109 |
| Number of pages | 6 |
| Volume | 2015-January |
| ISBN (Electronic) | 9781479983421 |
| DOIs | |
| Publication status | Published - Mar 10 2015 |
| Event | 2015 International Conference on Information Networking, ICOIN 2015 - Siem Reap, Cambodia Duration: Jan 12 2015 → Jan 14 2015 |
Other
| Other | 2015 International Conference on Information Networking, ICOIN 2015 |
|---|---|
| Country | Cambodia |
| City | Siem Reap |
| Period | 1/12/15 → 1/14/15 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Information Systems
Cite this
Detection of Android ad library focusing on HTTP connections and view object redraw behaviors. / Kajiwara, Naoya; Kawamoto, Junpei; Matsumoto, Shinichi; Hori, Yoshiaki; Sakurai, Kouichi.
2015 International Conference on Information Networking, ICOIN 2015. Vol. 2015-January IEEE Computer Society, 2015. p. 104-109 7057865.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Detection of Android ad library focusing on HTTP connections and view object redraw behaviors
AU - Kajiwara, Naoya
AU - Kawamoto, Junpei
AU - Matsumoto, Shinichi
AU - Hori, Yoshiaki
AU - Sakurai, Kouichi
PY - 2015/3/10
Y1 - 2015/3/10
N2 - In recent years, the smart phone application market has expanded rapidly. One of reasons is the popularity of free applications. A developer acquires his revenues by including advertising libraries in his own application. However, some problems about these advertising libraries become clear from recent researches. Especially in the leakage of privacy information is known as a typical problem which advertising libraries cause. In order to solve this problem, the technology which detects advertisement libraries is important. In this paper, we propose a method for detection of Android ad library. We focus on the acquisition and redraw of advertising image operation which are the basic operations of mobile advertisement. Firstly, we tried running some applications with advertisements. Then, It turned out that mobile advertisements acquire advertising images from server and set that image on the screen at a fixed interval. By modifying AndroidOS, logging HTTP connections and View object redraw behaviors, we confirmed the ad image acquisition behavior. Moreover, to take advantage of the periodicity of this behavior, we carried out Fourier-transform the invocation time data of HTTP connections and redraw of View objects. Then, we extracted the periodicity by calculating correlation coefficient for these two data. From the value of correlation coefficient, it is possible to judge whether advertisement library is incorporated into an application or not. As a result, our proposal method results in a output of about 76 % detection rate.
AB - In recent years, the smart phone application market has expanded rapidly. One of reasons is the popularity of free applications. A developer acquires his revenues by including advertising libraries in his own application. However, some problems about these advertising libraries become clear from recent researches. Especially in the leakage of privacy information is known as a typical problem which advertising libraries cause. In order to solve this problem, the technology which detects advertisement libraries is important. In this paper, we propose a method for detection of Android ad library. We focus on the acquisition and redraw of advertising image operation which are the basic operations of mobile advertisement. Firstly, we tried running some applications with advertisements. Then, It turned out that mobile advertisements acquire advertising images from server and set that image on the screen at a fixed interval. By modifying AndroidOS, logging HTTP connections and View object redraw behaviors, we confirmed the ad image acquisition behavior. Moreover, to take advantage of the periodicity of this behavior, we carried out Fourier-transform the invocation time data of HTTP connections and redraw of View objects. Then, we extracted the periodicity by calculating correlation coefficient for these two data. From the value of correlation coefficient, it is possible to judge whether advertisement library is incorporated into an application or not. As a result, our proposal method results in a output of about 76 % detection rate.
UR - http://www.scopus.com/inward/record.url?scp=84940539173&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84940539173&partnerID=8YFLogxK
U2 - 10.1109/ICOIN.2015.7057865
DO - 10.1109/ICOIN.2015.7057865
M3 - Conference contribution
AN - SCOPUS:84940539173
VL - 2015-January
SP - 104
EP - 109
BT - 2015 International Conference on Information Networking, ICOIN 2015
PB - IEEE Computer Society
ER -