A Novel PCA-Firefly Based XGBoost Classification Model for Intrusion Detection in Networks Using GPU
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Open Access
- 27 January 2020
- journal article
- research article
- Published by MDPI AG in Electronics
- Vol. 9 (2), 219
- https://doi.org/10.3390/electronics9020219
Abstract
The enormous popularity of the internet across all spheres of human life has introduced various risks of malicious attacks in the network. The activities performed over the network could be effortlessly proliferated, which has led to the emergence of intrusion detection systems. The patterns of the attacks are also dynamic, which necessitates efficient classification and prediction of cyber attacks. In this paper we propose a hybrid principal component analysis (PCA)-firefly based machine learning model to classify intrusion detection system (IDS) datasets. The dataset used in the study is collected from Kaggle. The model first performs One-Hot encoding for the transformation of the IDS datasets. The hybrid PCA-firefly algorithm is then used for dimensionality reduction. The XGBoost algorithm is implemented on the reduced dataset for classification. A comprehensive evaluation of the model is conducted with the state of the art machine learning approaches to justify the superiority of our proposed approach. The experimental results confirm the fact that the proposed model performs better than the existing machine learning models.Keywords
This publication has 21 references indexed in Scilit:
- Assessing rear-end collision risk of cars and heavy vehicles on freeways using a surrogate safety measureAccident Analysis & Prevention, 2018
- Adaptive and online network intrusion detection system using clustering and Extreme Learning MachinesJournal of the Franklin Institute, 2018
- Use of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for multivariate association between bioactive compounds and functional properties in foods: A critical perspectiveTrends in Food Science & Technology, 2018
- Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic CharacterizationPublished by INSTICC ,2018
- Hybrid Firefly-Bat Optimized Fuzzy Artificial Neural Network Based Classifier for Diabetes DiagnosisInternational Journal of Intelligent Engineering and Systems, 2017
- Cuckoo Search Optimized Reduction and Fuzzy Logic Classifier for Heart Disease and Diabetes PredictionInternational Journal of Fuzzy System Applications, 2017
- A Hybrid Scheme for Breast Cancer Detection using Intuitionistic Fuzzy Rough Set TechniqueInternational Journal of Healthcare Information Systems and Informatics, 2016
- Hybrids of support vector machine wrapper and filter based framework for malware detectionFuture Generation Computer Systems, 2016
- HIDS: A host based intrusion detection system for cloud computing environmentInternational Journal of System Assurance Engineering and Management, 2014
- A comparative study of RIFCM with other related algorithms from their suitability in analysis of satellite images using other supporting techniquesKybernetes, 2014