LiFE (Logical iOSForensics Examiner): An Open Source iOSBackup Forensics Examination Tool

In this paper, we present LiFE (Logical iOS Forensics Examiner), an open source iOS backup forensics examination tool. This tool helps both researchers and practitioners alike in both understanding the backup structures of iOS devices and forensically examining iOS backups. The tool is currently capable of parsing device information, call history, voice messages, GPS locations, conversations, notes, images, address books, calendar entries, SMS messages, Aux locations, facebook data and e-mails. The tool consists of both a manual interface (where the user is able to manually examine the backup structures) and an automated examination interface (where the tool pulls out evidence from known files). Additionally, LiFE is designed so that the evidence located in files would retain its integrity. It is important to note that most of the evidence examined by LiFE is parsed from SQLite databases that are backed up by iTunes. LiFE also offers an extensibility option to the user, where an examiner can add new evidence SQLite files to the application that can be automatically parsed, and these known files are then automatically populated in the automated GUI’s toolbar with an icon added to the investigator’s liking. Keywords: iOS forensics, Small Scale Digital Devices, iPhone forensics, iPad forensics, SQLite, Open source tools, iTunes backup, Extensible forensics software, File identification, LiF

Procedures and tools for acquisition and analysis of volatile memory on android smartphones

Mobile phone forensics have become more prominent since mobile phones have become ubiquitous both for personal and business practice. Android smartphones show tremendous growth in the global market share. Many researchers and works show the procedures and techniques for the acquisition and analysis the non-volatile memory inmobile phones. On the other hand, the physical memory (RAM) on the smartphone might retain incriminating evidence that could be acquired and analysed by the examiner. This study reveals the proper procedure for acquiring the volatile memory inthe Android smartphone and discusses the use of Linux Memory Extraction (LiME) for dumping the volatile memory. The study also discusses the analysis process of the memory image with Volatility 2.3, especially how the application shows its capability analysis. Despite its advancement there are two major concerns for both applications. First, the examiners have to gain root privileges before executing LiME. Second, both applications have no generic solution or approach. On the other hand, currently there is no other tool or option that might give the same result as LiME and Volatility 2.3

A comparison of forensic evidence recovery techniques for a windows mobile smart phone

<p>Acquisition, decoding and presentation of information from mobile devices is complex and challenging. Device memory is usually integrated into the device, making isolation prior to recovery difficult. In addition, manufacturers have adopted a variety of file systems and formats complicating decoding and presentation.</p> <p>A variety of tools and methods have been developed (both commercially and in the open source community) to assist mobile forensics investigators. However, it is unclear to what extent these tools can present a complete view of the information held on a mobile device, or the extent the results produced by different tools are consistent.</p> <p>This paper investigates what information held on a Windows Mobile smart phone can be recovered using several different approaches to acquisition and decoding. The paper demonstrates that no one technique recovers all information of potential forensic interest from a Windows Mobile device; and that in some cases the information recovered is conflicting.</p&gt