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System Call Analysis of Android Malware Families

机译:Android恶意软件家族的系统调用分析

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Background/Objectives: Now a days, Android Malware is coded so wisely that it has become very difficult to detect them. The static analysis of malicious code is not enough for detection of malware as this malware hides its method call in encrypted form or it can install the method at runtime. The system call tracing is an effective dynamic analysis technique for detecting malware as it can analyze the malware at the run time. Moreover, this technique does not require the application code for malware detection. Thus, this can detect that android malware also which are difficult to detect with static analysis of code. As Android was launched in 2008, so there were fewer studies available regarding the behavior of Android Malware Families and their characteristics. The aim of this work is to explore the behavior of 10 popular Android Malware Families focused on System Call Pattern of these families. Methods/Statistical Analysis: For this purpose, the authors have extracted the system call trace of 345 malicious applications from 10 Android Malware Families named FakeInstaller, Opfake, Plankton, DroidKungFu, BaseBridge, Iconosys, Kmin, Adrd and Gappusin using strace android tool and compared it with the system calls pattern of 300 Benign Applications to justify the behavior of malicious application. Findings: During the experiment, it is observed that the malicious applications invoke some system calls more frequently than benign applications. Different Android malware invokes the different set of system calls with different frequency. Applications/Improvements: This analysis can prove helpful in designing intrusion-detection systems for an android mobile device with more accuracy.
机译:背景/目标:如今,Android恶意软件的编码是如此明智,以至于很难检测到它们。对恶意代码进行静态分析不足以检测到恶意软件,因为该恶意软件以加密形式隐藏了其方法调用,或者可以在运行时安装该方法。系统调用跟踪是一种用于检测恶意软件的有效动态分析技术,因为它可以在运行时对其进行分析。而且,该技术不需要用于恶意软件检测的应用程序代码。因此,这可以检测到还无法通过静态代码分析检测到的android恶意软件。由于Android于2008年推出,因此有关Android恶意软件家族的行为及其特征的研究较少。这项工作的目的是探索针对这些系列的10个流行的Android恶意软件系列的行为。方法/统计分析:为此,作者使用strace android工具从10个名为FakeInstaller,Opfake,Plankton,DroidKungFu,BaseBridge,Iconosys,Kmin,Adrd和Gappusin的10个Android恶意软件家族中提取了345个恶意应用程序的系统调用跟踪,并进行了比较它使用300个“良性应用程序”的系统调用模式来证明恶意应用程序的行为是合理的。结果:在实验期间,发现恶意应用程序比良性应用程序更频繁地调用某些系统调用。不同的Android恶意软件以不同的频率调用不同的系统调用集。应用程序/改进:可以证明此分析对为Android移动设备设计更准确的入侵检测系统很有帮助。

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