Abstract

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.

Highlights

  • The worldwide use of mobile phone devices is increasing daily

  • This paper develops a Mobile Forensic Metamodel (MFM) in order to clarify all the necessary activities required by investigators for conducting their task

  • The purpose of extracting digital evidence from mobile phone devices is to use it in court proceedings, as these devices are frequently used in criminal activities [13]

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Summary

Introduction

The worldwide use of mobile phone devices is increasing daily. Ericsson President and CEO Hans Vestberg expects that by 2020, 50 billion mobile phones will be connected to the web as compared to five billion [1]. Mobile Device, Identification, Securing Scene, Evaluating Scene, Potential Digital Evidence, 62 Procedure, Seizure Device, Integrity, Preparing, Search, Documentation, Recording, Photographing, Evidence Collection, Memory Volatility, PackagingAndSealing, Transporting and Storing Evidence, Isolation, Faraday Cage, Decision, Filtering, Law Enforcement, Validation, Hidden Data Analysis, Equipment, Removable Media, Verification, Interviewing, Internal Memory, Forensic Examiner, Capturing, Forensic Specialist, Forensic Laboratory, Acquisition Method, Logical Acquisition, Physical Acquisition, Manual Extraction, Extraction, Recovering, Search Warrant, Forensic Tool, Examination Data, Copy of Evidence, Forensic Analyst, Potential Evidence, Suspect, Analysis Data, Hash Value, Application and File Analysis, Timeframe Analysis, Court of Law, Results, Evidence, Jurisdiction, Scene, Conclusion, Acquired Data, KeywordSearch, Source, Airplane Mode, Cell Site Analysis, Network Provider.

Background
Mobile forensic metamodel
Identification of common phases of domain
Model collection and classification
Concept extraction
Selection and identification of common concepts
Short-listing and reconciliation of definitions
Classification of common concept
Relationship identification among concepts
Metamodel validation
Result
Conclusion
Full Text
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