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ABC-BSRF: Artificial Bee Colony and Borderline-SMOTE RF Algorithm for Intrusion Detection System on Data Imbalanced Problem

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Proceedings of International Conference on Computational Intelligence and Data Engineering

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 56))

Abstract

In the current scenario, machine learning techniques are advantageous for making better decisions. They indeed are important and achieve better results in Intrusion Detection Systems (IDSs). Even though prominent classifiers may produce outstanding results regarding the majority classes, they are biased. Remarkably, the Imbalanced aspect of data leads to generate inaccurate results since the minority classes are not adjudicated properly and result in misclassification costs. In this paper, the classification problems due to imbalanced data are effectively addressed by the latest evolving techniques. To overcome this difficulty and improve the model performance, an acute algorithm, named Artificial Bee Colony Borderline SMOTE on Random Forests (ABC-BSRF) is proposed. It constitutes Artificial Bee Colony (ABC analysis) for Feature selection and Borderline SMOTE through random forests for oversampling. The results are compared with individual classifiers such as Support Vector Machines (SVMs), Decision Trees, and K-nearest neighbor (KNN). Observed results inferred from the experimentations done on KDD cup 99 dataset have proved that our proposed work can be excellently resolving the issue of imbalanced data. The ROC curve, F1 score, Precision, Recall, and AUC have shown noticeable results in contrast with other traditional methods.

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Authors and Affiliations

  1. Vardhaman College of Engineering, Shamshabad, Hyderabad, Telangana, India

    Pullagura Indira priyadarsini

Authors
  1. Pullagura Indira priyadarsini
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Correspondence to Pullagura Indira priyadarsini .

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Editors and Affiliations

  1. University of Calcutta, Kolkata, India

    Nabendu Chaki

  2. West Pomeranian University of Technology, Szczecin, Poland

    Jerzy Pejas

  3. VIT-AP University, Amaravati, India

    Nagaraju Devarakonda

  4. Vasavi College of Engineering, Hyderabad, India

    Ram Mohan Rao Kovvur

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priyadarsini, P.I. (2021). ABC-BSRF: Artificial Bee Colony and Borderline-SMOTE RF Algorithm for Intrusion Detection System on Data Imbalanced Problem. In: Chaki, N., Pejas, J., Devarakonda, N., Rao Kovvur, R.M. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-15-8767-2_2

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