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Database Intrusion Detection Using Adaptive Resonance Network Theory Model

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Computational Intelligence in Data Mining

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 990))

Abstract

In the current automation world, every organizations starting from education to industry and also in research organization are maintaining database and several security breaches are found in these databases. Traditional database security mechanism cannot handle the malicious access toward database. Although, various researches have been done in database intrusion detection, but most of the researches are limited in efficiency and accuracy. Inspired by human cognitive system, we present a database intrusion detection system using Adaptive Resonance Theory which is accompanied with some data mining techniques for preprocessing data. The proposed model can learn easily and cope up with the dynamic environment which entitles the system to detect both known and unknown patterns accurately with low false positive cost. The calculated simulation result shows that the database intrusion detection based on Adaptive Resonance Theory can accelerate the detection process with higher accuracy as compared to Self Organizing Map and Radial basis functional neural network.

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Author information

Authors and Affiliations

  1. Department of Computer Science & Engineering, Veer Surendra Sai University of Technology, Burla, Odisha, India

    Anitarani Brahma & Suvasini Panigrahi

Authors
  1. Anitarani Brahma
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  2. Suvasini Panigrahi
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Corresponding author

Correspondence to Anitarani Brahma .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

  3. Department of Computer Application, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India

    Bighnaraj Naik

  4. Faculty of Communication Sciences, University of Teramo, Teramo, Italy

    Danilo Pelusi

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Brahma, A., Panigrahi, S. (2020). Database Intrusion Detection Using Adaptive Resonance Network Theory Model. In: Behera, H., Nayak, J., Naik, B., Pelusi, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 990. Springer, Singapore. https://doi.org/10.1007/978-981-13-8676-3_22

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