Data Mining Usage in Corporate Information Security: Intrusion Detection Applications
Al Quhtani Masoud ()
Additional contact information
Al Quhtani Masoud: Embassy of the Kingdom of Saudi Arabia in Bosnia and Herzegovina, Sarajevo, Bosnia and Herzegovina
Business Systems Research, 2017, vol. 8, issue 1, 51-59
Abstract:
Background: The globalization era has brought with it the development of high technology, and therefore new methods of preserving and storing data. New data storing techniques ensure data are stored for longer periods of time, more efficiently and with a higher quality, but also with a higher data abuse risk. Objective: The goal of the paper is to provide a review of the data mining applications for the purpose of corporate information security, and intrusion detection in particular. Methods/approach: The review was conducted using the systematic analysis of the previously published papers on the usage of data mining in the field of corporate information security. Results: This paper demonstrates that the use of data mining applications is extremely useful and has a great importance for establishing corporate information security. Data mining applications are directly related to issues of intrusion detection and privacy protection. Conclusions: The most important fact that can be specified based on this study is that corporations can establish a sustainable and efficient data mining system that will ensure privacy and successful protection against unwanted intrusions.
Keywords: data mining; instruction; privacy; corporate information security (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://doi.org/10.1515/bsrj-2017-0005 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bit:bsrysr:v:8:y:2017:i:1:p:51-59:n:5
DOI: 10.1515/bsrj-2017-0005
Access Statistics for this article
Business Systems Research is currently edited by Mirjana Pejić Bach
More articles in Business Systems Research from Sciendo
Bibliographic data for series maintained by Peter Golla ().