Ben Martini

Mohammad Shariati, Ali Dehghantanha1, Ben Martini et al.

STorage as a Service (STaaS) cloud services has been adopted by both individuals and businesses as a dominant technology worldwide. Similar to other technologies, this widely accepted service can be misused by criminals. Investigating cloud platforms is becoming a standard component of contemporary digital investigation cases. Hence, digital forensic investigators need to have a working knowledge of the potential evidence that might be stored on cloud services. In this chapter, we conducted a number of experiments to locate data remnants of users' activities when utilizing the Ubuntu One cloud service. We undertook experiments based on common activities performed by users on cloud platforms including downloading, uploading, viewing, and deleting files. We then examined the resulting digital artifacts on a range of client devices, namely, Windows 8.1, Apple Mac OS X, and Apple iOS. Our examination extracted a variety of potentially evidential items ranging from Ubuntu One databases and log files on persistent storage to remnants of user activities in device memory and network traffic.

Quang Do, Ben Martini, Kim-Kwang Raymond Choo

In this paper, we propose an adversary model to facilitate forensic investigations of mobile devices (e.g. Android, iOS and Windows smartphones) that can be readily adapted to the latest mobile device technologies. This is essential given the ongoing and rapidly changing nature of mobile device technologies. An integral principle and significant constraint upon forensic practitioners is that of forensic soundness. Our adversary model specifically considers and integrates the constraints of forensic soundness on the adversary, in our case, a forensic practitioner. One construction of the adversary model is an evidence collection and analysis methodology for Android devices. Using the methodology with six popular cloud apps, we were successful in extracting various information of forensic interest in both the external and internal storage of the mobile device.

Ben Martini, Quang Do, Kim-Kwang Raymond Choo

Using the evidence collection and analysis methodology for Android devices proposed by Martini, Do and Choo, we examined and analyzed seven popular Android cloud-based apps. Firstly, we analyzed each app in order to see what information could be obtained from their private app storage and SD card directories. We collated the information and used it to aid our investigation of each app database files and AccountManager data. To complete our understanding of the forensic artefacts stored by apps we analyzed, we performed further analysis on the apps to determine if the user authentication credentials could be collected for each app based on the information gained in the initial analysis stages. The contributions of this research include a detailed description of artefacts, which are of general forensic interest, for each app analyzed.