https://digitalcommons.newhaven.edu/cgi/viewcontent.cgi?article=1016&context=electricalcomputerengineering-facpubs

Forensic analysis of social networking applications on mobile devices

A survey of information security incident handling in the cloud

A concise (no more than 200 words) and factual abstract is required. This should be on a separate page following the title page and should not contain reference citations. Graphical abstract Although a graphical abstract is optional, its use is encouraged as it draws more attention to the online article. The graphical abstract should summarize the contents of the article in a concise, pictorial form designed to capture the attention of a wide readership. Graphical abstracts should be submitted as a separate file in the online submission system. Image size: Please provide an image with a minimum of 531 × 1328 pixels (h × w) or proportionally more. The image should be readable at a size of 5 × 13 cm using a regular screen resolution of 96 dpi. Preferred file types: TIFF, EPS, PDF or MS Office files. You can view Example Graphical Abstracts on our information site. Authors can make use of Elsevier's Illustration Services to ensure the best presentation of their images and in accordance with all technical requirements. Highlights Highlights are mandatory for this journal. They consist of a short collection of bullet points that convey the core findings of the article and should be submitted in a separate editable file in the online submission system. Please use 'Highlights' in the file name and include 3 to 5 bullet points (maximum 85 characters, including spaces, per bullet point). You can view example Highlights on our information site.

Aggression and violent behavior

https://digitalcommons.newhaven.edu/cgi/viewcontent.cgi?article=1003&context=electricalcomputerengineering-facpubs

Network and device forensic analysis of Android social-messaging applications

The rapid growth in usage and application of Social Networking (SN) platforms make them a potential target by cyber criminals to conduct malicious activities such as identity theft, piracy, illegal trading, sexual harassment, cyber stalking and cyber terrorism. Many SN platforms are extending their services to mobile platforms, making them an important source of evidence in cyber investigation cases. Therefore, understanding the types of potential evidence of users’ SN activities available on mobile devices is crucial to forensic investigation and research. In this paper, we examine four popular SN applications: Facebook, Twitter, LinkedIn and Google+, on Android and iOS platforms, to detect remnants of users’ activities that are of forensic interest. We detect a variety of artefacts (e.g. usernames, passwords, login information, personal information, uploaded posts, exchanged messages and uploaded comments from SN applications) that could facilitate a criminal investigation.

Investigating Social Networking applications on smartphones detecting Facebook, Twitter, LinkedIn and Google+ artefacts on Android and iOS platforms

The paper investigates the effectiveness of the privacy mode feature in three widely used Web browsers, and outlines how to investigate when these browsers have been used to perform a criminal or illegal act. It performs an identical test on a privacy mode session for each of the three Web browsers and investigates whether traces are left behind. The analysis is done in three phases. First, common places where history and cache records are usually stored are examined. Then, other locations on the local machine are examined using special forensic tools. Also, the physical memory (RAM) is captured and examined for traces.

Forensic analysis of private browsing artifacts

This paper highlights the importance of Facebook's instant messaging service (Facebook Chat) as a potential source of evidence in an investigation. The paper discusses the process of recovering and reconstructing artifacts left by the use of Facebook Chat on a computer's hard disk. The paper describes experiments in which Facebook Chat conversations in Latin and Arabic character sets were conducted using three major web browsers, and then forensically retrieved. The results highlight how Facebook Chat artifacts of Arabic conversations can be difficult to locate with keyword search functions. The paper describes appropriate steps to overcome these difficulties.

Forensic artifacts of Facebook's instant messaging service

Behavioural Digital Forensics Model: Embedding Behavioural Evidence Analysis into the investigation of digital crimes

The utility of Behavioural Evidence Analysis (BEA) has gained attention in the field of Digital Forensics in recent years. It has been recognized that, along with technical examination of digital evidence, it is important to learn as much as possible about the individuals behind an offence, the victim (s) and the dynamics of a crime. This can assist the investigator in producing a more accurate and complete reconstruction of the crime, in interpreting associated digital evidence, and with the description of investigative findings. Despite these potential benefits, the literature shows limited use of BEA for the investigation of cases of the possession and dissemination of Sexually Exploitative Imagery of Children (SEIC). This paper represents a step towards filling this gap. It reports on the forensic analysis of 15 SEIC cases involving P2P file sharing networks, obtained from the Dubai Police. Results confirmed the predicted benefits and indicate that BEA can assist digital forensic practitioners and prosecutors.

/pdf/behavioural-evidence-analysis-applied-to-digital-forensics-2piqxjah6y.pdf

Noora Al Mutawa

Papers

Forensic analysis of social networking applications on mobile devices

Forensic analysis of private browsing artifacts

Forensic artifacts of Facebook's instant messaging service

Behavioural Digital Forensics Model: Embedding Behavioural Evidence Analysis into the investigation of digital crimes

Behavioural Evidence Analysis Applied to Digital Forensics: An Empirical Analysis of Child Pornography Cases Using P2P Networks