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

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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.

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APA

Kalinin, M., Krundyshev, V., & Zegzhda, D. (2021). AI Methods for Neutralizing Cyber Threats at Unmanned Vehicular Ecosystem of Smart City. In Studies on Entrepreneurship, Structural Change and Industrial Dynamics (pp. 157–171). Springer Nature. https://doi.org/10.1007/978-3-030-59959-1_10

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