Above: (L) Mr. Elmer C. Matel, the presenter, (R) Mr. Matel together with the session chair and other paper presenters
Last November 28 to December 1, 2019, Mr. Elmer C. Matel presented his paper entitled “Optimization of Network Intrusion Detection System Using Genetic Algorithm with Improved Feature Selection Technique”. This paper aims to optimize the performance of intrusion detection rate in a network using Genetic Algorithm with improved feature selection (GA-IFS) to efficiently identify cyber-attacks and other anomalies on the website. It offers a real-time feedback mechanism regarding the system evaluation of the current network traffic.
The novelty of this research paper lies in the following: (1) application of dataset pre-processing procedure to improve the convergence time of the Genetic Algorithm in dealing with the search space; (2) application of improved feature selection technique to decrease the false positive (false alarm) and false negative (incorrect) detection rate of cyber-attacks and (3) test the performance of the enhanced Genetic Algorithm in terms of detection speed and true positive (correct) detection rate. This paper got a positive impression from the peer reviewers, panel of reactors and co-presenters.
The 11th HNICEM or IEEE HNICEM 2019 was organized by the IEEE Computational Intelligence Society, Philippines Chapter. All published research articles are submitted to IEEExplore and indexed in SCOPUS.