Data Mining and Intrusion Detection Systems

Abstract

The rapid evolution of technology and the increased connectivity among its components, imposes new cyber-security challenges. To tackle this growing trend in computer attacks and respond threats, industry professionals and academics are joining forces in order to build Intrusion Detection Systems (IDS) that combine high accuracy with low complexity and time efficiency. The present article gives an overview of existing Intrusion Detection Systems (IDS) along with their main principles. Also this article argues whether data mining and its core feature which is knowledge discovery can help in creating Data mining based IDSs that can achieve higher accuracy to novel types of intrusion and demonstrate more robust behaviour compared to traditional IDSs.

Authors and Affiliations

Zibusiso Dewa, Leandros A. Maglaras

Keywords

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  • EP ID EP106758
  • DOI 10.14569/IJACSA.2016.070109
  • Views 107
  • Downloads 0

How To Cite

Zibusiso Dewa, Leandros A. Maglaras (2016). Data Mining and Intrusion Detection Systems. International Journal of Advanced Computer Science & Applications, 7(1), 62-71. https://europub.co.uk./articles/-A-106758