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IJET International Journal of Engineering and Technology E-ISSN 2227-524X

An Efficient Ids Based on Fuzzy Firefly Optimization and Fast Learning Network

Abstract

Overseen Interruption Recognition Framework is a framework that has the capacity of picking up from cases about past attacks to perceive new strikes. Using ANN based interruption discovery is promising for decreasing the amount of false negative or false positives in light of the fact that ANN has the capacity of picking up from certified cases. In this article, a made learning model for Quick Learning System (FLN) in light of fluffy firefly streamlining (FFO) has been proposed and named as FF-FLN. The model has been associated with the issue of interruption location and endorsed in perspective of the famous dataset KDD99. Our created strategy has been taken a gander at against a broad assortment of meta-heuristic figurings for planning ELM, and FLN classifier. FF-FLN has defeated other learning approaches in the testing exactness of the learning.

Authors and Affiliations

  • Bh Dasaradha Ram
  • B. V. Subba Rao

About this article

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Keywords

  • Fast learning network
  • IDS
  • Fuzzy Firefly’s
  • ANN.

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How to Cite

Dasaradha Ram, B., & V. Subba Rao, B. (2018). An Efficient Ids Based on Fuzzy Firefly Optimization and Fast Learning Network. International Journal of Engineering and Technology, 7(4.36), 557-561. https://doi.org/10.14419/ijet.v7i4.36.24137