Constructing a cybersecurity big data and data presentation solution
Cheryl Ann Alexander
Institute for IT Innovation and Smart Health
Lidong Wang
Institute for Systems Engineering Research, Mississippi State University
DOI: https://doi.org/10.59429/ifr.v2i1.6381
Keywords: cybersecurity; cyberattack; information infusion; big data; big data analytics; deep learning (DL); healthcare
Abstract
This paper introduces the requirements of Big Data analytics for cybersecurity, and the challenges of Big Data analytics in cybersecurity are highlighted. Methods and technologies used for the cybersecurity of big data are presented. The cybersecurity of big data in healthcare is introduced. Deep learning (DL) has been used in big data and cybersecurity. The applications of DL in cybersecurity and healthcare are summarized, including examples of tasks and specific DL method(s) for each task. The cybersecurity of big data in a medical center is presented as a case study. In today’s highly technological healthcare environment, big data cybersecurity in healthcare is primarily through data encryption for both data at rest and data in motion. The healthcare industry utilizes encryption to protect the sensitive information included in the clinical chart so that only authorized users and recipients are able to view and read the data. Cybercriminals are typically unable to read the data because they lack the decryption key.
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