Digital forensics readiness in big data networks: a novel framework and incident response script for Linux-Hadoop environments
Article
Mpungu, C., George, C. and Mapp, G. 2024. Digital forensics readiness in big data networks: a novel framework and incident response script for Linux-Hadoop environments. Applied System Innovation. 7 (5). https://doi.org/10.3390/asi7050090
Type | Article |
---|---|
Title | Digital forensics readiness in big data networks: a novel framework and incident response script for Linux-Hadoop environments |
Authors | Mpungu, C., George, C. and Mapp, G. |
Abstract | The surge in big data and analytics has catalysed the proliferation of cybercrime, largely driven by organisations’ intensified focus on gathering and processing personal data for profit while often overlooking security considerations. Hadoop and its derivatives are prominent platforms for managing big data; however, investigating security incidents within Hadoop environments poses intricate challenges due to scale, distribution, data diversity, replication, component complexity, and dynamicity. This paper proposes a big data digital forensics readiness framework and an incident response script for Linux–Hadoop environments, streamlining preliminary investigations. The framework offers a novel approach to digital forensics in the domains of big data and Hadoop environments. A prototype of the incident response script for Linux–Hadoop environments was developed and evaluated through comprehensive functionality and usability testing. The results demonstrated robust performance and efficacy. |
Keywords | Digital forensics; Digital forensics readiness; Incident response; Big data; Hadoop; Linux |
Sustainable Development Goals | 9 Industry, innovation and infrastructure |
Middlesex University Theme | Health & Wellbeing |
Research Group | ALERT Research Group |
Publisher | MDPI AG |
Journal | Applied System Innovation |
ISSN | |
Electronic | 2571-5577 |
Publication dates | |
Online | 25 Sep 2024 |
Oct 2024 | |
Publication process dates | |
Submitted | 17 Jul 2024 |
Accepted | 23 Sep 2024 |
Deposited | 25 Sep 2024 |
Output status | Published |
Publisher's version | License File Access Level Open |
Copyright Statement | Copyright: © 2024 by the authors. Published by MDPI on behalf of the International Institute of Knowledge Innovation and Invention. Licensee MDPI, Basel, Switzerland. |
Web address (URL) | https://www.mdpi.com/2571-5577/7/5/90 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/asi7050090 |
Language | English |
https://repository.mdx.ac.uk/item/17645w
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