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Data Mining Usage in Corporate Information Security: Intrusion Detection Applications

Author

Listed:
  • Al Quhtani Masoud

    (Embassy of the Kingdom of Saudi Arabia in Bosnia and Herzegovina, Sarajevo, Bosnia and Herzegovina)

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.

Suggested Citation

  • Al Quhtani Masoud, 2017. "Data Mining Usage in Corporate Information Security: Intrusion Detection Applications," Business Systems Research, Sciendo, vol. 8(1), pages 51-59, March.
    • Handle: RePEc:bit:bsrysr:v:8:y:2017:i:1:p:51-59:n:5
    DOI: 10.1515/bsrj-2017-0005
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    References listed on IDEAS

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    1. Willison , Robert, 2006. "Understanding the Perpetration of Employee Computer Crime in the Organisational Context," Working Papers 2006-4, Copenhagen Business School, Department of Informatics.
    2. B Baesens & C Mues & D Martens & J Vanthienen, 2009. "50 years of data mining and OR: upcoming trends and challenges," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 16-23, May.
    3. Stoel, M. Dale & Muhanna, Waleed A., 2011. "IT internal control weaknesses and firm performance: An organizational liability lens," International Journal of Accounting Information Systems, Elsevier, vol. 12(4), pages 280-304.
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    Cited by:

    1. Kenda Klemen & Mladenić Dunja, 2018. "Autonomous Sensor Data Cleaning in Stream Mining Setting," Business Systems Research, Sciendo, vol. 9(2), pages 69-79, July.

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