Digital Forensics Subdomains: The State of the Art and Future Directions
For reliable digital evidence to be admitted in a court of law, it is important to apply scientifically proven digital forensic investigation techniques to corroborate a suspected security incident. Mainly, traditional digital forensics techniques focus on computer desktops and servers. However, rec...
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2021
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oai:doaj.org-article:42e5dcde5c244180a3fced59c3e5f64d2021-11-20T00:02:37ZDigital Forensics Subdomains: The State of the Art and Future Directions2169-353610.1109/ACCESS.2021.3124262https://doaj.org/article/42e5dcde5c244180a3fced59c3e5f64d2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9594835/https://doaj.org/toc/2169-3536For reliable digital evidence to be admitted in a court of law, it is important to apply scientifically proven digital forensic investigation techniques to corroborate a suspected security incident. Mainly, traditional digital forensics techniques focus on computer desktops and servers. However, recent advances in digital media and platforms have seen an increased need for the application of digital forensic investigation techniques to other subdomains. This includes mobile devices, databases, networks, cloud-based platforms, and the Internet of Things (IoT) at large. To assist forensic investigators to conduct investigations within these subdomains, academic researchers have attempted to develop several investigative processes. However, many of these processes are domain-specific or describe domain-specific investigative tools. Hence, in this paper, we hypothesize that the literature is saturated with ambiguities. To further synthesize this hypothesis, a digital forensic model-orientated Systematic Literature Review (SLR) within the digital forensic subdomains has been undertaken. The purpose of this SLR is to identify the different and heterogeneous practices that have emerged within the specific digital forensics subdomains. A key finding from this review is that there are process redundancies and a high degree of ambiguity among investigative processes in the various subdomains. As a way forward, this study proposes a high-level abstract metamodel, which combines the common investigation processes, activities, techniques, and tasks for digital forensics subdomains. Using the proposed solution, an investigator can effectively organize the knowledge process for digital investigation.Arafat Al-DhaqmRichard Adeyemi IkuesanVictor R. KebandeShukor Abd RazakGeorge GrisposKim-Kwang Raymond ChooBander Ali Saleh Al-RimyAbdulrahman A. AlsewariIEEEarticleDigital forensicsdatabase forensicsmobile forensicnetwork forensicsIoT forensicsdigital forensic metamodelElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 152476-152502 (2021) |
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Digital forensics database forensics mobile forensic network forensics IoT forensics digital forensic metamodel Electrical engineering. Electronics. Nuclear engineering TK1-9971 |
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Digital forensics database forensics mobile forensic network forensics IoT forensics digital forensic metamodel Electrical engineering. Electronics. Nuclear engineering TK1-9971 Arafat Al-Dhaqm Richard Adeyemi Ikuesan Victor R. Kebande Shukor Abd Razak George Grispos Kim-Kwang Raymond Choo Bander Ali Saleh Al-Rimy Abdulrahman A. Alsewari Digital Forensics Subdomains: The State of the Art and Future Directions |
description |
For reliable digital evidence to be admitted in a court of law, it is important to apply scientifically proven digital forensic investigation techniques to corroborate a suspected security incident. Mainly, traditional digital forensics techniques focus on computer desktops and servers. However, recent advances in digital media and platforms have seen an increased need for the application of digital forensic investigation techniques to other subdomains. This includes mobile devices, databases, networks, cloud-based platforms, and the Internet of Things (IoT) at large. To assist forensic investigators to conduct investigations within these subdomains, academic researchers have attempted to develop several investigative processes. However, many of these processes are domain-specific or describe domain-specific investigative tools. Hence, in this paper, we hypothesize that the literature is saturated with ambiguities. To further synthesize this hypothesis, a digital forensic model-orientated Systematic Literature Review (SLR) within the digital forensic subdomains has been undertaken. The purpose of this SLR is to identify the different and heterogeneous practices that have emerged within the specific digital forensics subdomains. A key finding from this review is that there are process redundancies and a high degree of ambiguity among investigative processes in the various subdomains. As a way forward, this study proposes a high-level abstract metamodel, which combines the common investigation processes, activities, techniques, and tasks for digital forensics subdomains. Using the proposed solution, an investigator can effectively organize the knowledge process for digital investigation. |
format |
article |
author |
Arafat Al-Dhaqm Richard Adeyemi Ikuesan Victor R. Kebande Shukor Abd Razak George Grispos Kim-Kwang Raymond Choo Bander Ali Saleh Al-Rimy Abdulrahman A. Alsewari |
author_facet |
Arafat Al-Dhaqm Richard Adeyemi Ikuesan Victor R. Kebande Shukor Abd Razak George Grispos Kim-Kwang Raymond Choo Bander Ali Saleh Al-Rimy Abdulrahman A. Alsewari |
author_sort |
Arafat Al-Dhaqm |
title |
Digital Forensics Subdomains: The State of the Art and Future Directions |
title_short |
Digital Forensics Subdomains: The State of the Art and Future Directions |
title_full |
Digital Forensics Subdomains: The State of the Art and Future Directions |
title_fullStr |
Digital Forensics Subdomains: The State of the Art and Future Directions |
title_full_unstemmed |
Digital Forensics Subdomains: The State of the Art and Future Directions |
title_sort |
digital forensics subdomains: the state of the art and future directions |
publisher |
IEEE |
publishDate |
2021 |
url |
https://doaj.org/article/42e5dcde5c244180a3fced59c3e5f64d |
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