Title: A forensic evidence recovery from mobile device applications

Authors: John K. Alhassan; Agbejule Gbolahan; Ismaila Idris; Shafi'i Muhammad Abdulhamid; Victor O. Waziri

Addresses: Department of Cyber Security Science, Federal University of Technology, Minna, Nigeria ' Department of Cyber Security Science, Federal University of Technology, Minna, Nigeria ' Department of Cyber Security Science, Federal University of Technology, Minna, Nigeria ' Department of Cyber Security Science, Federal University of Technology, Minna, Nigeria ' Department of Cyber Security Science, Federal University of Technology, Minna, Nigeria

Abstract: In recent past, there are a lot of research advancements in mobile forensics tools. This is so due to increase usage of mobile phones in storage of information, law enforcement, mobile online transactions, and also negatively by criminals due to increased computational capabilities. Mobile forensics devices continue to remain a very challenging task due to poor user data retrieval techniques for evidence retrieval. Recently, third party applications assume a veritable feet because it is supported by majority of mobile devices platforms, thereby making it easy to extract information of its users' for future criminal audit. This paper proposes an evidence data retrieval method from InstagramApp using two networks-based platforms [that is, pure peer-to-peer (PPP) and special cluster peer (SCP)-based], whose concept is to manage mobile device communication and generate multiple copies of users data/information to be dumped across three servers. The forensic test results were obtained from PPP and SCP developed to securely extract data from mobile devices. This shows that, SCP outperformed PPP in terms of the time taken to fulfil forensic auditor's request, throughput and broadband utilisation which are 42.82% to 57.18%, 56.81% to 43.19% and 35.41% to 64.53% respectively.

Keywords: mobile forensic; evidence recovery; pure peer-to-peer; special cluster peer; SCP; mobile device.

DOI: 10.1504/IJDET.2018.092633

International Journal of Digital Enterprise Technology, 2018 Vol.1 No.1/2, pp.79 - 95

Received: 24 Apr 2017
Accepted: 09 Oct 2017
Published online: 26 Jun 2018 *