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Cited by 264

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Big data security and privacy in healthcare: A Review

Open access
Abouelmehdi, Karim, Beni-Hssane, Abderrahim, Khaloufi, Hayat, Saadi, Mostafa·2017·Procedia Computer Science

Abstract

The ever-increasing integration of highly diverse enabled data generating technologies in medical, biomedical and healthcare fields and the growing availability of data at the central location that can be used in need of any organization from pharmaceutical manufacturers to health insurance companies to hospitals have primarily make healthcare organizations and all its sub-sectors in face of a flood of big data as never before experienced. While this data is being hailed as the key to improving health outcomes, gain valuable insights and lowering costs, the security and privacy issues are so overwhelming that healthcare industry is unable to take full advantage of it with its current resources. Managing and harnessing the analytical power of big data, however, is vital to the success of all healthcare organizations. It is in this context that this paper aims to present the state-of-the-art security and privacy issues in big data as applied to healthcare industry and discuss some available data privacy, data security, users’ accessing mechanisms and strategies.

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Metadata

Authors
Abouelmehdi, K., Beni-Hssane, A., Khaloufi, H., & Saadi, M.
Venue
Procedia Computer Science
Publisher
Elsevier BV
Published
2017
Volume
113
Pages
73-80
ISSN
1877-0509 (ISSN-L)
OpenAlex
W2756289758
Cited by
264
References
25
FWCI
7.88
Type
conference paper
Language
en
Open access
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CoChat. (2026). Citation check: Big data security and privacy in healthcare: A Review. https://app.cochat.ai/papers/10.1016/j.procs.2017.08.292
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Abouelmehdi, K., Beni-Hssane, A., Khaloufi, H., & Saadi, M. (2017). Big data security and privacy in healthcare: A Review. Procedia Computer Science. https://doi.org/10.1016/j.procs.2017.08.292

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.