A Digital Evidence Taxonomy of M-Health Apps in IoT Environment
Muhammad Thariq Abdul Razak1, Nurul Hidayah Ab Rahman2, Nurul Azma Abdullah3
1Muhammad Thariq Abdul Razak, Information Security Interest Group (ISIG), Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia.
2Nurul Hidayah Ab Rahman, Information Security Interest Group (ISIG), Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia.
3Nurul Azma Abdullah, Information Security Interest Group (ISIG), Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia.
Manuscript received on 25 March 2019 | Revised Manuscript received on 04 April 2019 | Manuscript Published on 27 April 2019 | PP: 285-290 | Volume-7 Issue-6S2 April 2019 | Retrieval Number: F10440476S219/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The adoption of IoT in enabling mobile health (m-health) apps created threats platform to the black hat hackers to compromise sensitive information (e.g. User personal detail, medicine data and outdoor activities) available from the apps. The heterogeneous nature of IoT infrastructure, however, would complicate activities of digital forensics. Therefore, we proposed a model of digital evidence taxonomy of m-health apps in IoT environment. The model includes evidence acquisitions and analysis at three layers of IoT such as mobile, application, and network layer. 34 top rating Android m-health apps were applied in a controlled experiment to examine the usability of the proposed model. Our results present fully, partially and none recovered evidence artifacts from the three layers as well as the analysis of forensic interest. This suggests that applying the model would facilitate forensic investigation activities and enable a forensically ready environment.
Keywords: Digital Forensics; Forensic by Design: Forensic Readiness; Forensic Taxonomy; Internet of Things (IoT); IoT Forensics.
Scope of the Article: IoT