A Forensics Memory Study of Malware in Android Operating Systems

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I. INTRODUCTION

A

ndroid operated devices are one of the most competitive technology devices in the market, with the fastest growing market share within the mobile industry [1]. Technology experts predict that it will dominate the mobile market in the coming decade. Additionally, recent research shows a huge year over year increase in the number of Android specific malware attacks [1,3]. It is relatively straightforward to investigate such attacks when they occur on mature operating system platforms such as Windows and Linux. However, due to the immaturity of Android memory image forensics, it is relatively problematic and time consuming to conduct such investigations on Android systems. In this research, we take advantage of recent advances in Android memory forensics technologies to explore a sample of these malware attacks, utilizing the open source digital forensics Volatility, a powerful investigation framework written in Python, capable of reading memory images from different Android kernel versions, and capable of performing a wide range of memory analysis and digital evidence extraction.

Volatility analyzes memory images, which must be extracted from the physical memory of the Android device, these images are extracted using Linux Memory Extractor “LiME” [12], to this moment, I`m not aware of any other Android memory image extractor. This loadable kernel module can acquire the full memory address range from an Android system, either over the network or via an SdCard [10]. Along with various new Android specific Volatility plugins, and a custom built ARM architecture investigation profile for Volatility, these tools are used in our research to analyze running malware through the exploration of hidden processes, process...

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[23] Anderson, David. (2003,2008). White paper: Red Hat Crash Utility. Redhat Software Inc. [Online] Available: http://people.redhat.com/anderson/crash_whitepaper/

[24] Haruyama, Takahiro. ( July 04, 2013). Windows Memory Forensics Analysis using Encase. [Online] Available: http://www.slideshare.net/takahiroharuyama5/takahiro-haruyama-ceic20110515

[25] Juanru Li. Dawu Gu. yuhao Lua. (2012). Android Malware Forensics: Reconstruction of Malicious Events: Dept of Computer Science and Engineering, Shanghai Jiao Tong University. [Online] Available: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6258204

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