Mobile Devices Forensics Investigation: Process Models and Comparison

Sadiq, Muhammad; Iqbal, Muhammad Shahid; Sajad, Muhammad Anwar; Naveed, Khawar; Malip, Amizah

doi:10.15863/tas.2016.01.33.29

Cited by 8 publications

(2 citation statements)

References 7 publications

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“…For example, the concepts " Incident " in models [ 43 , 50 ], " Case " in model [ 52 ] and " Crime " in models [ 45 , 47 , 48 , 55 , 59 , 61 ] have similar meaning. Hence, we grouped these concepts into one common concept: “ Crime ”, as shown in Table 4 .In addition, the concepts that have a single name such as “ Securing Scene ” in models [ 42 , 45 , 46 , 48 , 59 , 61 ] are considered as common concept. The remainder of selection of common concepts are shown in S1 Table .…”

Section: Mobile Forensic Metamodelmentioning

confidence: 99%

A metamodel for mobile forensics investigation domain

et al. 2017

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With the rapid development of technology, mobile phones have become an essential tool in terms of crime fighting and criminal investigation. However, many mobile forensics investigators face difficulties with the investigation process in their domain. These difficulties are due to the heavy reliance of the forensics field on knowledge which, although a valuable resource, is scattered and widely dispersed. The wide dispersion of mobile forensics knowledge not only makes investigation difficult for new investigators, resulting in substantial waste of time, but also leads to ambiguity in the concepts and terminologies of the mobile forensics domain. This paper developed an approach for mobile forensics domain based on metamodeling. The developed approach contributes to identify common concepts of mobile forensics through a development of the Mobile Forensics Metamodel (MFM). In addion, it contributes to simplifying the investigation process and enables investigation teams to capture and reuse specialized forensic knowledge, thereby supporting the training and knowledge management activities. Furthermore, it reduces the difficulty and ambiguity in the mobile forensics domain. A validation process was performed to ensure the completeness and correctness of the MFM. The validation was conducted using two techniques for improvements and adjustments to the metamodel. The last version of the adjusted metamodel was named MFM 1.2.

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Section: Mobile Forensic Metamodelmentioning

confidence: 99%

A metamodel for mobile forensics investigation domain

et al. 2017

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“…In the study conducted by Sadiq et al, some of the previously used mobile forensic examination models were reviewed and existing models was compared [7]. The advantage of the proposed model is the combination of the extra and repeated stages and stages of the previous models.…”

Section: Related Workmentioning

confidence: 99%

Forensic Analysis of Popular Social Media Applications on Android Smartphones

Eriş

Akbal

2021

Balkan Journal of Electrical and Computer Engineering

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The use of mobile devices as an evidence of crime has increased. Social network forensics is a branch of science that includes accessing and analyzing many personal data that may contain evidence on social networks. Considering the multiplicity of personal data artefact by social networking applications in mobile devices, the importance of examining social media applications in mobile devices emerges. In this study, the necessary processes for the forensic investigation of mobile devices are examined, the necessary procedures for data extraction from mobile devices are explained and it is revealed how the analysis of social media applications in terms of forensic information in mobile devices should be realized. In the application part of the study, the most widely used mobile operating systems on android devices with android operating prompts; Facebook, WhatsApp Messenger, Instagram, Twitter applications have been installed, basic user behavior analysis of devices that have been performed. During the investigation phase, Oxygen Forensic, Paraben E3: DS and Magnet Axiom were used as tools for manual data extraction and mobile forensic information. The obtained data by both methods are shown comparatively.

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