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AI Methods for Neutralizing Cyber Threats at Unmanned Vehicular Ecosystem of Smart City

In: The Economics of Digital Transformation

Author

Listed:
  • Maxim Kalinin

    (Peter the Great St.Petersburg Polytechnic University)

  • Vasiliy Krundyshev

    (Peter the Great St.Petersburg Polytechnic University)

  • Dmitry Zegzhda

    (Peter the Great St.Petersburg Polytechnic University)

Abstract

Due to the increased mobility of the infrastructural topology and the growing amount of data being processed, traditional protection methods become ineffective. Security weaknesses cause disruption of control, malfunction of transportation, the occurrence of smart building equipment failures, traffic jams, etc. New methods to ensure cyber security for new digital platforms are required. The article analyzes the existing approaches to ensuring cyber security in modern dynamic networks and revealed their main advantages and disadvantages. The authors propose the application of new AI methods (swarm algorithms and neural networks) to ensure the security of the network in the infrastructure of the intelligent transport system (ITS) a sample of new digital platforms. The paper assesses the possibility of their use for preventing cyber threats in the digital infrastructures of V2X. The results of experiments to assess the effectiveness of the proposed approach, obtained using supercomputer modeling are given. The achievements are ready for application in other smart environments: IoT, IIoT, WSN, mesh networks, and m2m-networks.

Suggested Citation

  • Maxim Kalinin & Vasiliy Krundyshev & Dmitry Zegzhda, 2021. "AI Methods for Neutralizing Cyber Threats at Unmanned Vehicular Ecosystem of Smart City," Studies on Entrepreneurship, Structural Change and Industrial Dynamics, in: Tessaleno Devezas & João Leitão & Askar Sarygulov (ed.), The Economics of Digital Transformation, edition 1, pages 157-171, Springer.
    • Handle: RePEc:spr:seschp:978-3-030-59959-1_10
    DOI: 10.1007/978-3-030-59959-1_10
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