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Intrusion Detection Using Navie Bayes by Analyzing Big Data

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  • B. Geetha Kumari
  • Jageti Padmavthi

Abstract

Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.

Suggested Citation

  • B. Geetha Kumari & Jageti Padmavthi, 2017. "Intrusion Detection Using Navie Bayes by Analyzing Big Data," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(6), pages 469-474, December.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i6:id:hcseit1726149
    Note: Article URL: https://ijsrcseit.com/CSEIT1726149
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