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The System for Operational Monitoring and Analytics of Industry Cyber-Physical Systems Security in Fuel and Energy Domains Based on Anomaly Detection and Prediction Methods

  • N. V. Nashivochnikov
  • Alexander A. Bolshakov
  • A. A. LukashinEmail author
  • M. Popov
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 260)

Abstract

The distinctive features and key areas of analytical tools application for the operational monitoring and security analysis of cyber-physical systems of critical information infrastructure are highlighted. Problems of applying data analytics methods and technologies to ensure the security of cyber-physical systems at enterprises of the fuel and energy industries are described. The architectural solutions of the advanced security analytics platform are proposed. The chapter discusses the use of data analysis methods and technologies to ensure the security of cyber-physical systems at enterprises of the fuel and energy complex. Identified the distinctive features and highlighted the key areas of application of analytical tools of the system of operational monitoring and security analysis of cyber-physical systems of critical information infrastructure. Problem questions are formulated, the possibilities and limitations of advanced analytics tools in solving the tasks of ensuring the security of cyber-physical systems at the enterprises of the fuel and energy complex are defined. Architectural solutions of the advanced cybersecurity analytics platform are described. The presented results are based on the analysis of information from open sources: materials of scientific-practical conferences, analytical and technical reviews on the subject of security of industrial systems, and generalization of practical experience in the development, implementation, and support of integrated security systems at enterprises of the fuel and energy complex.

Keywords

Data analysis practices Anomaly detection SIEM Advanced analytics platform Machine learning Import substitution Operational monitoring and analysis system 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • N. V. Nashivochnikov
    • 1
  • Alexander A. Bolshakov
    • 1
  • A. A. Lukashin
    • 2
    Email author
  • M. Popov
    • 2
  1. 1.Gazinformservice Ltd.St. PetersburgRussia
  2. 2.Peter the Great St. Petersburg Polytechnic UniversitySt. PetersburgRussia

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