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Detection of Android ad library focusing on HTTP connections and view object redraw behaviors

机译:检测针对HTTP连接并查看对象重绘行为的Android广告库

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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.
机译:近年来,智能手机应用市场迅速扩大。原因之一是免费应用程序的普及。开发商通过在他自己的申请中包括广告图书馆来获取他的收入。然而,关于这些广告图书馆的一些问题来自最近的研究变得清楚。特别是在隐私信息的泄漏中被称为广告图书馆原因的典型问题。为了解决这个问题,检测广告库的技术很重要。在本文中,我们提出了一种检测Android广告库的方法。我们专注于广告图像操作的收购和重绘,这是移动广告的基本操作。首先,我们尝试使用广告运行一些应用程序。然后,事实证明,移动广告从服务器获取广告图像并以固定间隔在屏幕上设置该图像。通过修改Androidos,记录HTTP连接和查看对象Redraw行为,我们确认了广告图像采集行为。此外,为了利用这种行为的周期性,我们执行了傅里叶 - 转换了HTTP连接的调用时间数据和视图对象的重绘。然后,我们通过计算这两个数据的相关系数来提取周期性。根据相关系数的值,可以判断广告库是否被纳入应用程序。结果,我们的提议方法导致输出约76%的检测率。

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