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Poster Abstract: Highlighting Easily How Malicious Applications Corrupt Android Devices

机译:海报摘要:轻松突出恶意应用程序如何损坏Android设备

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We propose an approach based on information flows to highlight how a malicious application corrupts an Android device. Basic attacks carried on by malicious applications often consist in leaking sensitive data to remote entities. Different works then focused on approaches to detect such attacks by analysing function calls or the access and the use of sensitive data (e.g). However, there exist an other class of attack that threatens the integrity of the system itself or data it contains (e.g modification of the content of sensitive files or installation of new application). Such attacks tend to be overlooked and we propose here an approach to easily detect and highlight them. To highlight these attacks, we first monitor how information from an application under analysis is disseminated in the whole system thanks to an information flow monitor named Blare. Blare monitors information flow between system objects (process, file and socket) at system level and logs observed flow. Prom the log, we build a System Flow Graph that describes the observed flows in a compact format. We then filter the edges of the SFG to only keep odd flows. As Android applications are all built in the same way, they have common behaviours, which means that some information flows they cause are the same (e.g information flow with the system_server process). By removing from the SFG the edges that describe information flows that are also present in SFG of benign applications, we therefore get the suspicious flows that can characterize an attack. We test our approach on 4 pieces of malware publicly known for corrupting Android devices and show that remaining edges of their SFGs describes the attack they are carrying.
机译:我们提出一种基于信息流的方法,以突出显示恶意应用程序如何损坏Android设备。恶意应用程序进行的基本攻击通常包括将敏感数据泄漏到远程实体。然后,不同的工作侧重于通过分析函数调用或敏感数据(例如)的访问和使用来检测此类攻击的方法。但是,还存在另一种攻击类型,它们威胁着系统本身或其中包含的数据的完整性(例如,修改敏感文件的内容或安装新的应用程序)。此类攻击往往被忽略,我们在此提出一种轻松检测并突出显示它们的方法。为了强调这些攻击,我们首先借助名为Blare的信息流监控器来监控来自被分析应用程序的信息如何在整个系统中传播。 Blare在系统级别监视系统对象(进程,文件和套接字)之间的信息流,并记录观察到的流。提示日志,我们构建一个系统流程图,以紧凑格式描述观察到的流量。然后,我们过滤SFG的边缘以仅保留奇数流。由于Android应用程序都是以相同的方式构建的,因此它们具有共同的行为,这意味着它们导致的某些信息流是相同的(例如,使用system_server进程的信息流)。通过从SFG中删除描述良性应用程序SFG中也存在的信息流的边缘,因此,我们获得了可表征攻击的可疑流。我们对4种以破坏Android设备而闻名的恶意软件测试了该方法,并证明其SFG的其余边缘描述了他们所遭受的攻击。

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