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Network Attack Detection with QNNBADT in Minimal Response Times Using Minimized Features

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Computer Networks and Inventive Communication Technologies

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 75))

Abstract

Internet is a medium of globally interconnected independent networks. Though it was created to interconnect government research laboratories in 1994, it has witnessed phenomenal growth and has expanded to service millions of users in governments, academia and public/private organizations for multitude of purposes. Internet has been evolving continuously. Internet has also evidenced many attacks on its networks called cyberattacks. As Internet evolves, adversaries also evolve in their attacking techniques making it imperative to guard networks from attacks. In spite of firewalls, AVs (Anti Viruses) and other defense mechanisms, there is an implicit need to monitor deliberate proliferations. IDSs (Intrusion Detection Systems) are techniques that help monitor networks and raise alarms on finding damaging proliferations. This also implies IDSs need to be quick in their assessments of malicious behavior on the network. This paper proposes a NN (Neural Network) based IDS that can quickly respond to attacks by analyzing low-level network details. The proposed scheme is evaluated on the In CIRA-CIC-DoHBrw-2020 dataset where it averagely scores above 90% in accuracy when benchmarked on different sample sizes.

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Authors and Affiliations

  1. Department of Computational Logistics, Alagappa University, Karaikudi, India

    S. Ramakrishnan & A. Senthil Rajan

Authors
  1. S. Ramakrishnan
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  2. A. Senthil Rajan
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Editor information

Editors and Affiliations

  1. Department of Information Technology, RVS Technical Campus, Coimbatore, Tamil Nadu, India

    S. Smys

  2. Department of Telecommunication Engineering, Czech Technical University in Prague, Praha, Czech Republic

    Robert Bestak

  3. Gerald Schwartz School of Business, St. Francis Xavier University, Antigonish, NS, Canada

    Ram Palanisamy

  4. Faculty of Informatics and Information Technology, Slovak University Technology, Bratislava, Slovakia

    Ivan Kotuliak

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Ramakrishnan, S., Senthil Rajan, A. (2022). Network Attack Detection with QNNBADT in Minimal Response Times Using Minimized Features. In: Smys, S., Bestak, R., Palanisamy, R., Kotuliak, I. (eds) Computer Networks and Inventive Communication Technologies . Lecture Notes on Data Engineering and Communications Technologies, vol 75. Springer, Singapore. https://doi.org/10.1007/978-981-16-3728-5_43

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  • DOI: https://doi.org/10.1007/978-981-16-3728-5_43

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-3727-8

  • Online ISBN: 978-981-16-3728-5

  • eBook Packages: EngineeringEngineering (R0)

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