The case for validating ADDIE model as a digital forensic model for peer to peer network investigation

Journal article


Musa, A., Awan, I-U and Zarah, F. 2022. The case for validating ADDIE model as a digital forensic model for peer to peer network investigation. Information System Frontiers. https://doi.org/10.1007/s10796-022-10360-8
AuthorsMusa, A., Awan, I-U and Zarah, F.
Abstract

Rapid technological advancement can substantially impact the processes of digital forensic investigation and present a myriad of challenges to the investigator. With these challenges, it is necessary to have a standard digital forensic framework as the foundation of any digital investigation. State-of-the-art digital forensic models assume that it is safe to move from one investigation stage to the next. It guides the investigators with the required steps and procedures. This brings a great stride to validate a non-specific framework to be used in most digital investigation procedures. This paper considers a new technique for detecting active peers that participate in a peer-to-peer (P2P) network. As part of our study, we crawled the μTorrent P2P client over ten days in different instances while logging all participating peers. We then employed digital forensic techniques to analyse the popular users and generate evidence within them with high accuracy. We evaluated our approach against the standard Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model for the digital investigation to achieve the credible digital evidence presented in this paper. Finally, we presented a validation case for the ADDIE model using the United States Daubert Test and the United Kingdom’s Forensic Science Regulator Guidance – 218 (FSR-G-218) and Forensic Science Regulator Guidance – 201 (FSR-G-201) to formulate it as a standard digital forensic model.

KeywordsValidation; ADDIE model; Digital forensics; Peer-to-peer network; Investigation
Year2022
JournalInformation System Frontiers
PublisherSpringer Nature
ISSN1387-3326
1572-9419
Digital Object Identifier (DOI)https://doi.org/10.1007/s10796-022-10360-8
Official URLhttps://link.springer.com/article/10.1007/s10796-022-10360-8
Publication dates
Print02 Dec 2022
Publication process dates
Accepted14 Nov 2022
Deposited12 Dec 2022
Accepted author manuscript
File Access Level
Open
Publisher's version
License
File Access Level
Open
Output statusPublished
Permalink -

https://repository.canterbury.ac.uk/item/934wz/the-case-for-validating-addie-model-as-a-digital-forensic-model-for-peer-to-peer-network-investigation

Download files

  • 10
    total views
  • 4
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Functional and performance analysis of discrete event network simulation tools
Musa, A. and Awan, I. 2022. Functional and performance analysis of discrete event network simulation tools. Simulation Modelling Practice and Theory. 116, p. 102470. https://doi.org/10.1016/j.simpat.2021.102470
Machine learning for intrusion detection and network performance
Ibrahim Abobaker and Ahmad Musa 2021. Machine learning for intrusion detection and network performance. in: 2021 8th International Conference on Future Internet of Things and Cloud (FiCloud)
Efficacy of ADDIE model in peer-to-peer networks: Digital evidence investigation
Ahmad Musa, Irfan-Ullah Awan and Ibrahim Abobaker 2021. Efficacy of ADDIE model in peer-to-peer networks: Digital evidence investigation. in: 2021 8th International Conference on Future Internet of Things and Cloud (FiCloud) IEEE.
Self regulated learning in flipped classrooms: A systematic literature review
Rasheed Abubakar Rasheed, Amirrudin Kamsin, Nor Aniza Abdullah, Habeebah Adamu Kakudi, Auwal Shehu Ali, Ahmad Musa and Adamu Sani Yahaya 2020. Self regulated learning in flipped classrooms: A systematic literature review. International Journal of Information and Education Technology. 10 (11). https://doi.org/10.18178/ijiet.2020.10.11.1469
An investigation into peer-to-peer network security using Wireshark
Ahmad Musa, Aliyu Abubakar, Usman Abdul Gimba and Rasheed Abubakar Rasheed 2019. An investigation into peer-to-peer network security using Wireshark. in: 2019 15th International Conference on Electronics, Computer and Computation (ICECCO) IEEE.
Transfer learning based histopathologic image classification for burns recognition
Aliyu Abubakar, Hassan Ugail, Ali Maina Bukar, Ali Ahmad Aminu and Ahmad Musa 2019. Transfer learning based histopathologic image classification for burns recognition. in: 2019 15th International Conference on Electronics, Computer and Computation (ICECCO) IEEE.