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A Real-Time Intrusion Detection System for Software Defined 5G Networks

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Advanced Information Networking and Applications (AINA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 227))

Abstract

The philosophy that founds the world of the Internet of Things apparently becomes essential for the projected permanently connected world. The 5G data networks are supposed to dramatically improve the actual 4G networks’ real world significance, which makes them fundamental for the next generation networks of IoT devices. The academic and industrial effort to improve the 5G technological standards considers various routes. Thus, this paper presents the state-of-the-art concerning the development of the standards that model the 5G networks. It values the authors’ experience that was gathered during the implementation of the Vodafone Romania 5G networked services. It puts this acquired experience in context by reviewing the relevant similar work, the relevant technologies, and it describes the research directions and difficulties that will probably influence the design and implementation of large 5G data networks. Consequently, the paper presents a machine learning-based real time intrusion detection system, which has been effectively tested in the context of a 5G data network. The intelligent intrusion detection system considers the creation of software defined networks, and it uses artificial intelligence based models. It is able to detect unknown intrusions through the usage of machine learning-based software components. The system has been assessed and the results prove that it achieves superior performance with a lower overhead in comparison to similar approaches, which allows it to be deployed on real-time 5G networks.

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Author information

Authors and Affiliations

  1. Transilvania University of Brasov, Brasov, Romania

    Razvan Bocu

  2. Caucasus University, Tbilisi, Georgia

    Maksim Iavich

  3. National University of Ireland, Cork, Ireland

    Sabin Tabirca

Authors
  1. Razvan Bocu
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  2. Maksim Iavich
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  3. Sabin Tabirca
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Corresponding author

Correspondence to Razvan Bocu .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Computer Science, Ryerson University, Toronto, ON, Canada

    Isaac Woungang

  3. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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Bocu, R., Iavich, M., Tabirca, S. (2021). A Real-Time Intrusion Detection System for Software Defined 5G Networks. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-030-75078-7_44

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