移动僵尸网络检测:概念验证

Zubaile Abdullah, M. Saudi, N. B. Anuar
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引用次数: 21

摘要

如今,像智能手机这样的移动设备已经被广泛使用。人们使用智能手机不仅限于打电话或发信息,还可以浏览网页、社交网络和网上银行交易。在某种程度上,所有的机密信息都保存在他们的智能手机里。因此,智能手机成为网络犯罪的主要目标之一,特别是通过安装移动僵尸网络。Eurograbber是移动僵尸网络的一个例子,它在受害者不知情的情况下通过受感染的移动应用程序安装。它会伪装成手机银行应用软件,窃取受害者智能手机上的金融交易信息。2012年,Eurograbber在全球累计造成了4700万美元的损失。基于这个僵尸网络所带来的影响,这就是这项研究的出发点。本文介绍了僵尸网络如何工作的概念证明以及正在进行的有效检测和响应移动僵尸网络的研究。利用逆向工程流程和静态分析技术对Crusewind僵尸网络代码进行分析,检测僵尸网络恶意活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobile botnet detection: Proof of concept
Nowadays mobile devices such as smartphones had widely been used. People use smartphones not limited for phone calling or sending messages but also for web browsing, social networking and online banking transaction. To certain extend, all confidential information are kept in their smartphone. As a result, smartphones became as one of the cyber-criminal main target especially through an installation of mobile botnet. Eurograbber is an example of mobile botnet that being installed via infected mobile application without victim knowledge. It will pretense as mobile banking application software and steal financial transaction information from victim's smartphone. In 2012, Eurograbber had caused a total loss of USD 47 Million accumulatively all over the world. Based on the implications posed by this botnet, this is the urge where this research comes in. This paper presents a proof of concept on how the botnet works and the ongoing research to detect and respond to the mobile botnet efficiently. Detection of botnet malicious activity is done through an analysis of Crusewind Botnet code using reverse engineering process and static analysis technique.
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