inis 18: e4

Research Article

Classification of UNSW-NB15 dataset using Exploratory Data Analysis using Ensemble Learning

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  • @ARTICLE{10.4108/eai.13-10-2021.171319,
        author={Neha Sharma and Narendra Singh Yadav and Saurabh Sharma},
        title={Classification of UNSW-NB15 dataset using Exploratory  Data Analysis using Ensemble Learning},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={INIS},
        year={2021},
        month={10},
        keywords={KDD’99, UNSW-NB15, Ensemble algorithms, XGBoost, AdaBoost, Random Forest, Extra trees},
        doi={10.4108/eai.13-10-2021.171319}
    }
    
  • Neha Sharma
    Narendra Singh Yadav
    Saurabh Sharma
    Year: 2021
    Classification of UNSW-NB15 dataset using Exploratory Data Analysis using Ensemble Learning
    INIS
    EAI
    DOI: 10.4108/eai.13-10-2021.171319
Neha Sharma1,*, Narendra Singh Yadav1, Saurabh Sharma2
  • 1: Manipal University Jaipur, Rajasthan- 303007, India
  • 2: Amity University Rajasthan, India
*Contact email: nehavaishnavisharma@gmail.com

Abstract

Recent advancements in machine learning have made it a tool of choice for different classification and analytical problems. This paper deals with a critical field of computer networking: network security and the possibilities of machine learning automation in this field. We will be doing exploratory data analysis on the benchmark UNSW-NB15 dataset. This dataset is a modern substitute for the outdated KDD’99 dataset as it has greater uniformity of pattern distribution. We will also implement several ensemble algorithms like Random Forest, Extra trees, AdaBoost, and XGBoost to derive insights from the data and make useful predictions. We calculated all the standard evaluation parameters for comparative analysis among all the classifiers used. This analysis gives knowledge, investigates difficulties, and future opportunities to propel machine learning in networking. This paper can give a basic understanding of data analytics in terms of security using Machine Learning techniques.