- Title
- Secure big data ecosystem architecture : challenges and solutions
- Creator
- Anwar, Memoona; Gill, Asif; Hussain, Farookh; Imran, Muhammad
- Date
- 2021
- Type
- Text; Journal article; Review
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/184629
- Identifier
- vital:16532
- Identifier
-
https://doi.org/10.1186/s13638-021-01996-2
- Identifier
- ISBN:1687-1472 (ISSN)
- Abstract
- Big data ecosystems are complex data-intensive, digital–physical systems. Data-intensive ecosystems offer a number of benefits; however, they present challenges as well. One major challenge is related to the privacy and security. A number of privacy and security models, techniques and algorithms have been proposed over a period of time. The limitation is that these solutions are primarily focused on an individual or on an isolated organizational context. There is a need to study and provide complete end-to-end solutions that ensure security and privacy throughout the data lifecycle across the ecosystem beyond the boundary of an individual system or organizational context. The results of current study provide a review of the existing privacy and security challenges and solutions using the systematic literature review (SLR) approach. Based on the SLR approach, 79 applicable articles were selected and analyzed. The information from these articles was extracted to compile a catalogue of security and privacy challenges in big data ecosystems and to highlight their interdependencies. The results were categorized from theoretical viewpoint using adaptive enterprise architecture and practical viewpoint using DAMA framework as guiding lens. The findings of this research will help to identify the research gaps and draw novel research directions in the context of privacy and security in big data-intensive ecosystems. © 2021, The Author(s).
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Relation
- Eurasip Journal on Wireless Communications and Networking Vol. 2021, no. 1 (2021), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- http://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright © The Author(s), 2021
- Rights
- Open Access
- Subject
- 4006 Communications engineering; 4606 Distributed computing and systems software; Big data; Big data ecosystem; Big data ecosystem challenges; Big data ecosystem privacy and security solutions; IoT; Privacy and security
- Full Text
- Reviewed
- Funder
- This research is supported by “Australian Government Research Training” Program Scholarship. Imran’s work is supported by the Deanship of Scientific Research at King Saud University through research group project number RG-1435-051.
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