Windows Surface RT tablet forensics

Small scale digital device forensics is particularly critical as a result of the mobility of these devices, leading to closer proximity to crimes as they occur when compared to computers. The Windows Surface tablet is one such device, combining tablet mobility with familiar Microsoft Windows productivity tools. This research considers the acquisition and forensic analysis of the Windows Surface RT tablet. We discuss the artifacts of both the Windows RT operating system and third-party applications. The contribution of this research is to provide a road map for the digital forensic examination of Windows Surface RT tablets.     

An Evidence‐based Forensic Taxonomy of Windows Phone Dating Apps

Advances in technologies including development of smartphone features have contributed to the growth of mobile applications, including dating apps. However, online dating services can be misused. To support law enforcement investigations, a forensic taxonomy that provides a systematic classification of forensic artifacts from Windows Phone 8 (WP8) dating apps is presented in this study. The taxonomy has three categories, namely: Apps Categories, Artifacts Categories, and Data Partition Categories. This taxonomy is built based on the findings from a case study of 28 mobile dating apps, using mobile forensic tools. The dating app taxonomy can be used to inform future studies of dating and related apps, such as those from Android and iOS platforms.     

A Forensic Exploration of the Microsoft Windows 10 Timeline

The Microsoft Windows operating system continues to dominate the desktop computing market. With such high levels of usage comes an inferred likelihood of digital forensic practitioners encountering this platform during their investigations. As part of any forensic examination of a digital device, operating system artifacts, which support the identification and understanding of how a user has behaved on their system provide a potential source of evidence. Now, following Microsoft's April 2018 build 1803 release with its incorporated “Timeline” feature, the potential for identifying and tracking user activity has increased. This work provides a timely examination of the Windows 10 Timeline feature demonstrating the ability to recover activity‐based content from within its stored database log files. Examination results and underpinning experimental methodologies are offered, demonstrating the ability to recover activity tile and process information in conjunction with the Windows Timeline. Further, an SQL query has been provided to support the interpretation of data stored within the ActivitiesCache.db .     

Forensic analysis of Telegram Messenger for Windows Phone

This article presents a forensic analysis methodology for obtaining the digital evidence generated by one of today's many instant messaging applications, namely “Telegram Messenger” for “Windows Phone”, paying particular attention to the digital forensic artifacts produced. The paper provides an overview of this forensic analysis, while focusing particularly on how the information is structured and the user, chat and conversation data generated by the application are organised, with the goal of extracting related data from the information. The application has several other features (e.g. games, bots, stickers) besides those of an instant messaging application (e.g. messages, images, videos, files). It is therefore necessary to decode and interpret the information, which may relate to criminal offences, and establish the relation of different types of user, chat and conversation.     

A reference database of Windows artifacts for file-wiping tool execution analysis

Anti-forensic technology can play an effective role in protecting information, but it can make forensic investigations difficult. Specifically, file-wiping permanently erases evidence, making it challenging for investigators to determine whether a file ever existed and prolonging the investigation process. To address this issue, forensic researchers have studied anti-forensic techniques that detect file-wiping activities. Many previous studies have focused on the effects of file-wiping tools on $MFT, $LogFile, and $DATA, rather than on Windows artifacts. Additionally, previous studies that have examined Windows artifacts have considered different artifacts, making it difficult to study them in a comprehensive manner. To address this, we focused on analyzing traces in 13 Windows artifacts of 10 file-wiping tools' operations in the Windows operating system comprehensively. For our experiments, we installed each file-wiping tool on separate virtual machines and checked the traces that the tools left behind in each artifact. We then organized the results in a database format. Our analysis revealed that most of the tools left traces on other artifacts, except for JumpList, Open&SavePidlMRU, and lnk. There were also some cases where traces remained on the other three artifacts. Based on our research, forensic investigators can quickly identify whether a file-wiping tool has been used, and it can assist in decision-making for evidence collection and forensic triage.     

An Evidence‐Based Forensic Taxonomy of Windows Phone Communication Apps

Communication apps can be an important source of evidence in a forensic investigation (e.g., in the investigation of a drug trafficking or terrorism case where the communications apps were used by the accused persons during the transactions or planning activities). This study presents the first evidence‐based forensic taxonomy of Windows Phone communication apps, using an existing two‐dimensional Android forensic taxonomy as a baseline. Specifically, 30 Windows Phone communication apps, including Instant Messaging (IM) and Voice over IP (VoIP) apps, are examined. Artifacts extracted using physical acquisition are analyzed, and seven digital evidence objects of forensic interest are identified, namely: Call Log, Chats, Contacts, Locations, Installed Applications, SMSs and User Accounts. Findings from this study would help to facilitate timely and effective forensic investigations involving Windows Phone communication apps.     

Forensic access to Windows Mobile pim.vol and other Embedded Database (EDB) volumes

Forensic examination of Windows Mobile devices and devices running its successor Windows Phone 7 remains relevant for the digital forensic community. In these devices, the file pim.vol is a Microsoft Embedded Database (EDB) volume that contains information related to contacts, appointments, call history, speed-dial settings and tasks. Current literature shows that analysis of the pim.vol file is less than optimal. We succeeded in reverse-engineering significant parts of the EDB volume format and this article presents our current understanding of the format. In addition we provide a mapping from internal column identifiers to human readable application-level property names for the pim.vol database. We implemented a parser and compared our results to the traditional approach using an emulator and the API provided by the Windows CE operating system. We were able to recover additional databases, additional properties per record and unallocated records.     

We are meeting on Microsoft Teams: Forensic analysis in Windows,Android, and iOS operating systems

Microsoft released a new communication platform, Microsoft Teams, in 2017. Due in part to COVID-19, the popularity of communication platforms, like Microsoft Teams, increased exponentially. Given its user base and increased popularity, it seems likely that digital forensic investigators will encounter cases where Microsoft Teams is a relevant component. However, because Microsoft Teams is a relatively new application, there is limited forensic research on the application particularly focusing on mobile operating systems. To address this gap, an analysis of data stored at rest by Microsoft Teams was conducted on the Windows 10 operating system as well as on Android and Apple iOS mobile operating systems. Basic functionalities, such as messaging, sharing files, participating in video conferences, and other functionalities that Teams provides, were performed in an isolated testing environment. Cellebrite UFED Physical Analyzer and Magnet AXIOM Examine tools were used to analyze the mobile devices and the Windows device, respectively. Manual or non-automated investigation recovered, at least partially, the majority of artifacts across all three operating systems. In this study, a total of 77.6% of the populated artifacts were partially or fully recovered in the manual investigation. On the other hand, forensic tools used did not automatically recover many of the artifacts found with the manual investigation. Only 13.8% of artifacts were partially or fully recovered by the forensic tools across all three devices. These discovered artifacts and the results of the investigations are presented in order to aid digital forensic investigations.     

Forensic acquisition and analysis of palm webOS on mobile devices

The emergence of webOS on Palm devices has created new challenges and opportunities for digital investigators. With the purchase of Palm by Hewlett Packard, there are plans to use webOS on an increasing number and variety of computer systems. These devices can store substantial amounts of information relevant to an investigation, including digital photographs, videos, call logs, SMS/MMS messages, e-mail, remnants of Web browsing and much more. Although some files can be obtained from such devices with relative ease, the majority of information of forensic interest is stored in databases on a system partition that many mobile forensic tools do not acquire. This paper provides a methodology for acquiring and examining forensic duplicates of user and system partitions from a device running webOS. The primary sources of digital evidence on these devices are covered with illustrative examples. In addition, the recovery of deleted items from various areas on webOS devices is discussed.     

USB Storage Device Forensics for Windows 10

Significantly increased use of USB devices due to their user‐friendliness and large storage capacities poses various threats for many users/companies in terms of data theft that becomes easier due to their efficient mobility. Investigations for such data theft activities would require gathering critical digital information capable of recovering digital forensics artifacts like date, time, and device information. This research gathers three sets of registry and logs data: first, before insertion; second, during insertion; and the third, after removal of a USB device. These sets are analyzed to gather evidentiary information from Registry and Windows Event log that helps in tracking a USB device. This research furthers the prior research on earlier versions of Microsoft Windows and compares it with latest Windows 10 system. Comparison of Windows 8 and Windows 10 does not show much difference except for new subkey under USB Key in registry. However, comparison of Windows 7 with latest version indicates significant variances.     

Forensic Investigation of Cooperative Storage Cloud Service: Symform as a Case Study

Researchers envisioned Storage as a Service (StaaS) as an effective solution to the distributed management of digital data. Cooperative storage cloud forensic is relatively new and is an under‐explored area of research. Using Symform as a case study, we seek to determine the data remnants from the use of cooperative cloud storage services. In particular, we consider both mobile devices and personal computers running various popular operating systems, namely Windows 8.1, Mac OS X Mavericks 10.9.5, Ubuntu 14.04.1 LTS, iOS 7.1.2, and Android KitKat 4.4.4. Potential artefacts recovered during the research include data relating to the installation and uninstallation of the cloud applications, log‐in to and log‐out from Symform account using the client application, file synchronization as well as their time stamp information. This research contributes to an in‐depth understanding of the types of terrestrial artifacts that are likely to remain after the use of cooperative storage cloud on client devices.     

Using jump lists to identify fraudulent documents

Jump lists show the file opening activity of a computer user. When a computer user wants to know the most recent file they opened, a jump list can provide that information. Windows 7 displays jump lists for recently used files, but more importantly for investigators, it also records hidden jump list artifacts. These hidden jump list artifacts reveal the complete trail a fraudster follows in creating fraudulent documents or to perform other illegal activities when using their computers. Such jump list artifacts can remain on the computer's drives for years. The paper describes a method that can be used to identify artifacts and their potential for use as forensic evidence in a financial fraud case.     

Private browsing: A window of forensic opportunity

The release of Internet Explorer 10 marks a significant change in how browsing artifacts are stored in the Windows file system, moving away from well-understood Index.dat files to use a high performance database, the Extensible Storage Engine. Researchers have suggested that despite this change there remain forensic opportunities to recover InPrivate browsing records from the new browser. The prospect of recovering such evidence, together with its potential forensic significance, prompts questions including where and when such evidence can be recovered, and if it is possible to prove that a recovered artefact originated from InPrivate browsing. This paper reports the results of experiments which answer these questions, and also provides some explanation of the increasingly complex data structures used to record Internet activity from both the desktop and Windows 8 Applications. We conclude that there is a time window between the private browsing session and the next use of the browser in which browsing records may be carved from database log files, after which it is necessary to carve from other areas of disk. It proved possible to recover a substantial record of a user's InPrivate browsing, and to reliably associate such records with InPrivate browsing.     

Automated Windows event log forensics

This paper proposes methods to automate recovery and analysis of Windows NT5 (XP and 2003) event logs for computer forensics. Requirements are formulated and methods are evaluated with respect to motivation and process models. A new, freely available tool is presented that, based on these requirements, automates the repair of a common type of corruption often observed in data carved NT5 event logs. This tool automates repair of multiple event logs in a single step without user intervention. The tool was initially developed to meet immediate needs of computer forensic engagements.Automating recovery, repair, and correlation of multiple logs make these methods more feasible for consideration in both a wider range of cases and earlier phases of cases, and hopefully, in turn, standard procedures. The tool was developed to fill a gap between capabilities of certain other freely available tools that may recover and correlate large volumes of log events, and consequently permit correlation with various other kinds of Windows artifacts. The methods are examined in the context of an example digital forensic service request intended to illustrate the kinds of civil cases that motivated this work.     

Reverse engineering of ReFS

File system forensics is an important part of Digital Forensics. Investigators of storage media have traditionally focused on the most commonly used file systems such as NTFS, FAT, ExFAT, Ext2-4, HFS+, APFS, etc. NTFS is the current file system used by Windows for the system volume, but this may change in the future. In this paper we will show the structure of the Resilient File System (ReFS), which has been available since Windows Server 2012 and Windows 8. The main purpose of ReFS is to be used on storage spaces in server systems, but it can also be used in Windows 8 or newer. Although ReFS is not the current standard file system in Windows, while users have the option to create ReFS file systems, digital forensic investigators need to investigate the file systems identified on a seized media. Further, we will focus on remnants of non-allocated metadata structures or attributes. This may allow metadata carving, which means searching for specific attributes that are not allocated. Attributes found can then be used for file recovery. ReFS uses superblocks and checkpoints in addition to a VBR, which is different from other Windows file systems. If the partition is reformatted with another file system, the backup superblocks can be used for partition recovery. Further, it is possible to search for checkpoints in order to recover both metadata and content.Another concept not seen for Windows file systems, is the sharing of blocks. When a file is copied, both the original and the new file will share the same content blocks. If the user changes the copy, new data runs will be created for the modified content, but unchanged blocks remain shared. This may impact file carving, because part of the blocks previously used by a deleted file might still be in use by another file. The large default cluster size, 64 KiB, in ReFS v1.2 is an advantage when carving for deleted files, since most deleted files are less than 64 KiB and therefore only use a single cluster. For ReFS v3.2 this advantage has decreased because the standard cluster size is 4 KiB.Preliminary support for ReFS v1.2 has been available in EnCase 7 and 8, but the implementation has not been documented or peer-reviewed. The same is true for Paragon Software, which recently added ReFS support to their forensic product. Our work documents how ReFS v1.2 and ReFS v3.2 are structured at an abstraction level that allows digital forensic investigation of this new file system. At the time of writing this paper, Paragon Software is the only digital forensic tool that supports ReFS v3.x.It is the most recent version of the ReFS file system that is most relevant for digital forensics, as Windows automatically updates the file system to the latest version on mount. This is why we have included information about ReFS v3.2. However, it is possible to change a registry value to avoid updating. The latest ReFS version observed is 3.4, but the information presented about 3.2 is still valid. In any criminal case, the investigator needs to investigate the file system version found.     

Analyzing Data Remnant Remains on User Devices to Determine Probative Artifacts in Cloud Environment

Cloud storage service allows users to store their data online, so that they can remotely access, maintain, manage, and back up data from anywhere via the Internet. Although helpful, this storage creates a challenge to digital forensic investigators and practitioners in collecting, identifying, acquiring, and preserving evidential data. This study proposes an investigation scheme for analyzing data remnants and determining probative artifacts in a cloud environment. Using pCloud as a case study, this research collected the data remnants available on end‐user device storage following the storing, uploading, and accessing of data in the cloud storage. Data remnants are collected from several sources, including client software files, directory listing, prefetch, registry, network PCAP, browser, and memory and link files. Results demonstrate that the collected remnants data are beneficial in determining a sufficient number of artifacts about the investigated cybercrime.     

A forensic examination of four popular cross‐platform file‐sharing apps with Wi‐Fi P2P

File‐sharing apps with Wi‐Fi hotspot or Wi‐Fi Direct functions become more popular. They can work on multiple platforms and allow users to transfer files in a concealed manner. However, when criminals use these apps in illegal activities, it becomes an important issue for investigators to find digital evidence on multiple platforms. At present, there are few studies on this topic, and most of them are limited to the single platform problem. In this paper, we propose a forensic examination method for four popular cross‐platform file‐sharing apps with Wi‐Fi hotspot and Wi‐Fi Direct functions: Zapya, SHAREit, Xender, and Feem. We use 22 static and live forensic tools for 11 platforms to acquire, analyze, and classify the forensic artifacts. In our experiments, we find many useful forensic artifacts and classify them into six categories. The experimental results can support law enforcement investigations of digital evidence and provide information for future studies on other cross‐platform file‐sharing apps.     

Media analyses based on Microsoft NTFS file ownership

The ever-increasing size of digital media presents a continuous challenge to digital investigators who must rapidly assess computer media to find and identify evidence. To meet this challenge, methods must continuously be sought to expedite the examination process. This paper investigates using the file ownership property as an analytical tool focusing on activity by individuals associated with the computer. Research centered on the New Technology File System (NTFS), which is the default file system in Microsoft Windows Operating System (OS). This was done because Microsoft's worldwide market penetration makes Windows and NTFS the most likely OS and file system to be encountered in digital forensic examinations. Significantly, digital forensic software now allows examination of NTFS file attributes and properties including the ownership property. The paper outlines potential limitations regarding interpreting ownership findings, and suggests areas for further research. Overall, file ownership is seen as a potentially viable new digital forensic tool.     

DigLA – A Digsby log analysis tool to identify forensic artifacts

Since the inception of Web 2.0, instant messaging, e-mailing, and social networking have emerged as cheap and efficient means of communication over the Web. As a result, a number of communication platforms like Digsby have been developed by various research groups to facilitate access to multiple e-mail, instant messaging, and social networking sites using a single credential. Although such platforms are advantageous for end-users, they present new challenges to digital forensic examiners because of their illegitimate use by anti-social elements. To identify digital artifacts from Digsby log data, an examiner is assumed to have knowledge of the whereabouts of Digsby traces before starting an investigation process. This paper proposes a design for a user-friendly GUI-based forensic tool, DigLA, which provides a unified platform for analyzing Digsby log data at different levels of granularity. DigLA is also equipped with password decryption methods for both machine-specific and portable installation versions of Digsby. By considering Windows registry and Digsby log files as dynamic sources of evidence, specifically when Digsby has been used to commit a cyber crime, this paper presents a systematic approach to analyzing Digsby log data. It also presents an approach to analyzing RAM and swap files to collect relevant traces, specifically the login credentials of Digsby and IM users. An expected insider attack from a server security perspective is also studied and discussed in this paper.     

Artifacts of CD burning in the Microsoft Windows master file table

When theft of a physical item occurs it is detectable by the fact that the object is missing, however, when the theft of a digital item occurs it can go unnoticed as exact replicas can be created. The original file is left intact but valuable information has been absconded. One of the challenges facing digital forensic examiners is detecting when files have been copied off of a computer system in some fashion. While certain methods do leave residual evidence behind, CD Burning has long been held as a copying method that cannot be identified. Through testing of the burning process and close examination of the New Technology File System (NTFS), artifacts from the master file table in the various versions of Microsoft Windows, markers have been found that are associated with copying or "burning" files to CD or DVD. Potential evidence that was once overlooked may now be detectable.