A Study on A Hybrid Approach of Genetic Algorithm & Fuzzy To Improve Anomaly or Intrusion

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 4

Abstract

Abstract: This paper describes a technique of applying Genetic Algorithm (GA) and fuzzy to network Intrusion Detection Systems (IDSs). A brief overview of a hybrid approach of genetic algorithm and fuzzy to improve anomaly or intrusion is presented. . This paper proposes genetic algorithm and fuzzy to generate that are able to detect anomalies and some specific intrusions. The goal of intrusion detection is to monitor network activities automatically, detect malicious attacks and to establish a proper architecture of the computer network security. Experimental results demonstrate that we can achieve better running time and accuracy with these modifications.

Authors and Affiliations

Er. Kamaldeep Kaur , Er. Simranjit Kaur Dhindsa

Keywords

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  • EP ID EP143082
  • DOI -
  • Views 106
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How To Cite

Er. Kamaldeep Kaur, Er. Simranjit Kaur Dhindsa (2015).  A Study on A Hybrid Approach of Genetic Algorithm & Fuzzy To Improve Anomaly or Intrusion. IOSR Journals (IOSR Journal of Computer Engineering), 17(4), 65-68. https://europub.co.uk/articles/-A-143082