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5G Cybersecurity Based on the Blockchain Random Neural Network in Intelligent Buildings

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Advances in Computational Intelligence Systems (UKCI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1043))

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Abstract

5G promises much faster Internet transmission rates at minimum latencies with indoor and outdoor coverage; 5G potentially could replace traditional Wi-Fi for network connectivity and Bluetooth technology for geolocation with a seamless radio coverage and network backbone that will accelerate new services such as the Internet of Things (IoT). New infrastructure applications will depend on 5G as a mobile Internet service provider therefore eliminating the need to deploy additional private network infrastructure or mobile networks to connect devices; however, this will increase cybersecurity risks as radio networks and mobile access channels will be shared between independent services. To address this issue, this paper presents a digital channel authentication method based on the Blockchain Random Neural Network to increase Cybersecurity against rogue 5G nodes; in addition, the proposed solution is applied to Physical Infrastructure: an Intelligent Building. The validation results demonstrate that the addition of the Blockchain Neural Network provides a cybersecure channel access control algorithm that identifies 5G rogue nodes where 5G node identities are kept cryptographic and decentralized.

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Author information

Authors and Affiliations

  1. Intelligent Systems and Networks Group, Electrical and Electronic Engineering, Alumni Imperial College London, London, UK

    Will Serrano

Authors
  1. Will Serrano
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Corresponding author

Correspondence to Will Serrano .

Editor information

Editors and Affiliations

  1. School of Computing, University of Portsmouth, Portsmouth, UK

    Zhaojie Ju

  2. Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK

    Longzhi Yang

  3. Bristol Robotics Laboratory, University of the West of England, Bristol, UK

    Chenguang Yang

  4. School of Computing, University of Portsmouth, Portsmouth, Hampshire, UK

    Alexander Gegov

  5. School of Computing, University of Portsmouth, Portsmouth, UK

    Dalin Zhou

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Serrano, W. (2020). 5G Cybersecurity Based on the Blockchain Random Neural Network in Intelligent Buildings. In: Ju, Z., Yang, L., Yang, C., Gegov, A., Zhou, D. (eds) Advances in Computational Intelligence Systems. UKCI 2019. Advances in Intelligent Systems and Computing, vol 1043. Springer, Cham. https://doi.org/10.1007/978-3-030-29933-0_34

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