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.     

The stalking victim's decision to contact the police: A test of Gottfredson and Gottfredson's theory of criminal justice decision making

There is a significant body of research exploring the reporting behaviors of crime victims. Much of this literature has focused on specific types of victimization (e.g., sexual assault) and the correlates of victim reporting. Recently, the crimes of stalking and cyberstalking have received empirical attention; however, few studies have examined the reporting behaviors of victims of these crimes. Using the theoretical framework proposed by Gottfredson and Gottfredson (1988), the current study explored how offense seriousness, the victim-offender relationship, and the prior record of the offender influenced a victim's decision to contact the police. Data were drawn from the 2006 stalking supplement to the National Crime Victimization Survey, which examined stalking in the United States. Results offered support to Gottfredson and Gottfredson (1988) and highlighted the significance of understanding the reporting behaviors for this sample of crime victims. Differences in reporting for victims of stalking and cyberstalking were also examined.     

Forensic analysis of WeChat on Android smartphones

WeChat is one of the most popular instant-messaging smartphone applications in the world. At the end of 2015, WeChat had 697 million monthly active users from over 200 countries. Although WeChat was designed originally for communication between relatives and friends, its abundant social functions are now also used by criminals for communication, and even for the organization and coordination of criminal acts. Therefore, communication records of social networking services like WeChat extracted from the smartphones of criminals are always the vital digital evidences for the investigation and prosecution of criminal cases. At present, only a few literatures focused on WeChat forensics. This paper describes several common questions that arise in forensic examinations of Android WeChat and provides corresponding technical methods that are useful to address these questions. This paper is intended to provide vital references for the investigators and researchers working on the digital forensics.     

A case study on anonymised sharing platforms and digital traces left by their usage

Non-local forms of file storage and transfer provide investigatory concerns. Whilst mainstream cloud providers offer a well-established challenge to those involved in criminal enquiries, there are also a host of services offering non-account based ‘anonymous’ online temporary file storage and transfer. From the context of a digital forensic investigation, the practitioner examining a suspect device must detect when such services have been utilised by a user, as offending files may not be resident on local storage media. In addition, identifying the use of a service may also expose networks of illegal file distribution, supporting wider investigations into criminal activity. This work examines 16 anonymous file transfer services and identifies and interprets the digital traces left behind on a device following their use to support law enforcement investigations.     

An Android Communication App Forensic Taxonomy

Due to the popularity of Android devices and applications (apps), Android forensics is one of the most studied topics within mobile forensics. Communication apps, such as instant messaging and Voice over IP (VoIP), are one popular app category used by mobile device users, including criminals. Therefore, a taxonomy outlining artifacts of forensic interest involving the use of Android communication apps will facilitate the timely collection and analysis of evidentiary materials from such apps. In this paper, 30 popular Android communication apps were examined, where a logical extraction of the Android phone images was collected using XRY, a widely used mobile forensic tool. Various information of forensic interest, such as contact lists and chronology of messages, was recovered. Based on the findings, a two‐dimensional taxonomy of the forensic artifacts of the communication apps is proposed, with the app categories in one dimension and the classes of artifacts in the other dimension. Finally, the artifacts identified in the study of the 30 communication apps are summarized using the taxonomy. It is expected that the proposed taxonomy and the forensic findings in this paper will assist forensic investigations involving Android communication apps.     

Protection Against Pursuit: A Conceptual and Empirical Comparison of Cyberstalking and Stalking Victimization Among a National Sample

Cyberstalking is a relatively understudied area in criminology, with no consensus among scholars as to whether it represents a modified form of stalking or whether it is an entirely new and emerging criminal phenomenon. Using data from the 2006 Supplemental Victimization Survey (SVS) to the National Crime Victimization Survey (NCVS), this study compares stalking and cyberstalking victims across several dimensions, including situational features of their experiences and self-protective behaviors. Results indicate that there are significant differences between stalking and cyberstalking victims, including their number of self-protective behaviors adopted, duration of contact with their stalker, financial costs of victimization, and perceived fear at onset. Perceived fear over time, the occurrence of a physical attack, and sex of the victim were all associated with a higher number of self-protective behaviors for cyberstalking victims compared to stalking victims, net of the effect of the control variables. Implications for stalking theory, research, and criminal justice policy are discussed.     

Incorporating index offence analysis into forensic clinical assessment

Purpose. Assessment is a core skill of clinical and forensic psychology practice and forms the basis of all ongoing engagements with offender/patients. In forensic settings, assessment involves the systematic gathering of reliable data on the characteristics of offenders and the offences which they have committed in order to develop understanding of the dynamics of offending and relevant intervention strategies. However, whilst the assessment process is aided by various protocols, no such instrument appears to exist for the assessment of an offender/patient's index offence. This paper presents a draft ‘index offence analysis guide’ designed by the present authors for this purpose and which has been piloted on prisoners and patients in secure settings. Argument. Evidence suggests that for various reasons, many clinicians do not routinely review crime scene data while working with offenders. However, this practice is arguably questionable, because how can decisions about admission, amenability to treatment, risk of reoffending, and discharge be made if there is limited awareness of what the offender/patient has done? The present authors argue that knowledge of the index offence is important to understanding the offender and suggest this can be obtained using a guide such as the one presented here. This is illustrated with an anonymous case. Conclusion. Index offence analysis should be a core task of any forensic clinician engaged in the assessment of offender/patients as it can provide a better understanding of crime scene actions and offence motivations. This can help guide treatment planning and improve risk assessments.     

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.     

Impacts of increasing volume of digital forensic data: A survey and future research challenges

A major challenge to digital forensic analysis is the ongoing growth in the volume of data seized and presented for analysis. This is a result of the continuing development of storage technology, including increased storage capacity in consumer devices and cloud storage services, and an increase in the number of devices seized per case. Consequently, this has led to increasing backlogs of evidence awaiting analysis, often many months to years, affecting even the largest digital forensic laboratories. Over the preceding years, there has been a variety of research undertaken in relation to the volume challenge. Solutions posed range from data mining, data reduction, increased processing power, distributed processing, artificial intelligence, and other innovative methods. This paper surveys the published research and the proposed solutions. It is concluded that there remains a need for further research with a focus on real world applicability of a method or methods to address the digital forensic data volume challenge.     

WhatsApp network forensics: Decrypting and understanding the WhatsApp call signaling messages

WhatsApp is a widely adopted mobile messaging application with over 800 million users. Recently, a calling feature was added to the application and no comprehensive digital forensic analysis has been performed with regards to this feature at the time of writing this paper. In this work, we describe how we were able to decrypt the network traffic and obtain forensic artifacts that relate to this new calling feature which included the: a) WhatsApp phone numbers, b) WhatsApp server IPs, c) WhatsApp audio codec (Opus), d) WhatsApp call duration, and e) WhatsApp's call termination. We explain the methods and tools used to decrypt the traffic as well as thoroughly elaborate on our findings with respect to the WhatsApp signaling messages. Furthermore, we also provide the community with a tool that helps in the visualization of the WhatsApp protocol messages.     

Triaging digital device content at-scene:- Formalising the decision-making process

The prominence of technology usage in society has inevitably led to increasing numbers of digital devices being seized, where digital evidence often features in criminal investigations. Such demand has led to well documented backlogs placing pressure on digital forensic labs, where in an effort to combat this issue, the ‘at-scene triage’ of devices has been touted as a solution. Yet such triage approaches are not straightforward to implement with multiple technical and procedural issues existing, including determining when it is actually appropriate to triage the contents of a device at-scene. This work remains focused on this point due to the complexities associated with it, and to support first responders a nine-stage triage decision model is offered which is designed to promote consistent and transparent practice when determining if a device should be triaged.     

“I couldn't find it your honour,it mustn't be there!” – Tool errors,tool limitations and user error in digital forensics

The field of digital forensics maintains significant reliance on the software it uses to acquire and investigate forms of digital evidence. Without these tools, analysis of digital devices would often not be possible. Despite such levels of reliance, techniques for validating digital forensic software are sparse and research is limited in both volume and depth. As practitioners pursue the goal of producing robust evidence, they face the onerous task of both ensuring the accuracy of their tools and, their effective use. Whilst tool errors provide one issue, establishing a tool's limitations also provides an investigatory challenge leading the potential for practitioner user-error and ultimately a grey area of accountability. This article debates the problems surrounding digital forensic tool usage, evidential reliability and validation.     

Forensic Taxonomy of Android Social Apps

An Android social app taxonomy incorporating artifacts that are of forensic interest will enable users and forensic investigators to identify the personally identifiable information (PII) stored by the apps. In this study, 30 popular Android social apps were examined. Artifacts of forensic interest (e.g., contacts lists, chronology of messages, and timestamp of an added contact) were recovered. In addition, images were located, and Facebook token strings used to tie account identities and gain access to information entered into Facebook by a user were identified. Based on the findings, a two‐dimensional taxonomy of the forensic artifacts of the social apps is proposed. A comparative summary of existing forensic taxonomies of different categories of Android apps, designed to facilitate timely collection and analysis of evidentiary materials from Android devices, is presented.     

Is cyberstalking different?

Abstract

Very little empirical work exists on cyberstalking. The current study analysed detailed questionnaires completed by 1051 self-defined stalking victims. Almost half (47.5%) reported harassment via the Internet, but only 7.2% of the sample was judged to have been cyberstalked. Ordinal regression analyses of four groups of victims, categorized according to degree of cyber involvement in their victimization, revealed a general picture of similarity between the groups in terms of the stalking process, responses to being stalked, and the effects on victims and third parties. It was concluded that cyberstalking does not fundamentally differ from traditional, proximal stalking, that online harassment does not necessarily hold broad appeal to stalkers, and that those who target ex-intimates remain the most populous stalker type.     

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.     

Placing the suspect at a PC: A preliminary study involving fingerprints on keyboards and mice

Digital devices now play an important role in the lives of many in society. Whilst they are used predominantly for legitimate purposes, instances of digital crime are witnessed, where determining their usage is important to any criminal investigation. Typically, when determining who has used a digital device, digital forensic analysis is utilised, however, biological trace evidence or fingerprints residing on its surfaces may also be of value. This work provides a preliminary study which examines the potential for fingerprint recovery from computer peripherals, namely keyboards and mice. Our implementation methodology is outlined, and results discussed which indicate that print recovery is possible. Findings are intended to support those operating at-scene in an evidence collection capacity.     

The COLLECTORS ranking scale for ‘at‐scene’ digital device triage

As digital evidence now features prominently in many criminal investigations, such large volumes of requests for the forensic examination of devices has led to well publicized backlogs and delays. In an effort to cope, triage policies are frequently implemented in order to reduce the number of digital devices which are seized unnecessarily. Often first responders are tasked with performing triage at scene in order to decide whether any identified devices should be seized and submitted for forensic examination. In some cases, this is done with the assistance of software which allows device content to be “previewed”; however, in some cases, a first responder will triage devices using their judgment and experience alone, absent of knowledge of the devices content, referred to as “decision‐based device triage” (DBDT). This work provides a discussion of the challenges first responders face when carrying out DBDT at scene. In response, the COLLECTORS ranking scale is proposed to help first responders carry out DBDT and to formalize this process in an effort to support quality control of this practice. The COLLECTORS ranking scale consists of 10 categories which first responders should rank a given device against. Each devices cumulative score should be queried against the defined “seizure thresholds” which offer support to first responders in assessing when to seize a device. To offer clarify, an example use‐case involving the COLLECTORS ranking scale is included, highlighting its application when faced with multiple digital devices at scene.     

A study on the forensic mechanisms of VoIP attacks: Analysis and digital evidence

This paper discusses the use of communication technology to commit crimes, including crime facts and crime techniques. The analysis focuses on the security of voice over Internet protocol (VoIP), a prevention method against VoIP call attack and the attention points for setting up an Internet phone. The importance of digital evidence and digital forensics are emphasised. This paper provides the VoIP digital evidence forensics standard operating procedures (DEFSOP) to help police organisations and establishes an experimental platform to simulate phone calls, hacker attacks and forensic data. Finally, this paper provides a general discussion of a digital evidence strategy that includes VoIP for crime investigators who are interested in digital evidence forensics.     

IoT forensics: Exploiting unexplored log records from the HIKVISION file system

CCTV surveillance systems are IoT products that can be found almost everywhere. Their digital forensic analysis often plays a key role in solving crimes. However, it is common for these devices to use proprietary file systems, which frequently hinders a complete examination. HIKVISION is a well-known manufacturer of such devices that typically ships its products with its proprietary file system. The HIKVISION file system has been analyzed before but that research has focused on the recovery of video footage. In this paper, the HIKVISION file system is being revisited regarding the log records it stores. More specifically, these log records are thoroughly examined to uncover both their structure and meaning. These unexplored pieces of evidence remain unexploited by major commercial forensic software, yet they can contain critical information for an investigation. To further assist digital forensic examiners with their analysis, a Python utility, namely the Hikvision Log Analyzer, was developed as part of this study that can automate part of the process.     

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.