Miner Alerts Module To Generate Itemsets Based On FP-Growth Algorithm Improvement

Authors

  • Karim Hashim Al-Saedi Al-Mustansiriyah University/College of Science
  • Raghda Abd Alrab Abd Alhassn Al-Mustansiriyah University/College of Science

DOI:

https://doi.org/10.23851/mjs.v29i1.286

Keywords:

Apriori Algorithm, Fp- Growth Algorithm, Data Mining, Network Security

Abstract

Data mining techniques becomes very useful for all areas, Which gives impressive results and accurate. It is can be works with huge data and variance types data. The intrusion detection system (IDS) has huge numbers of alerts without classify and almost alerts be false positive. In this paper, we proposed a new miner module to generating Itemsets of IDS alerts by using FP-Growth Algorithm Improvement, which it is produce from compact Fp growth algorithm with Apriori algorithm. This a new module contains three phases; Compute support, Resort, and Generating K-Itemsets. Its applies on Darpa 1999 datasets to generating Alerts sets based on IDS Snort. The obtain result was very useful because it is make the alerts ready to classify.

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Published

2018-10-31

How to Cite

[1]
K. H. Al-Saedi and R. A. A. Abd Alhassn, “Miner Alerts Module To Generate Itemsets Based On FP-Growth Algorithm Improvement”, MJS, vol. 29, no. 1, pp. 114–117, Oct. 2018.

Issue

Section

Computer Science