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Identification of Data Injection Attacks in Networked Control Systems Using Noise Impulse Integration.

Alan Oliveira de Sá1,2, António Casimiro3, Raphael C S Machado4,5

  • 1Admiral Wandenkolk Instruction Center, Brazilian Navy, Rio de Janeiro RJ 20180-003, Brazil.

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Summary
This summary is machine-generated.

This study introduces a novel cyberattack detection method for Networked Control Systems (NCS) in Industry 4.0. The Backtracking Search Optimization Algorithm (BSA) with Noise Impulse Integration (NII) effectively identifies malicious data injection attacks without disrupting normal operations.

Keywords:
countermeasuredata injection attackindustrial control systemnetworked control systemsecuritysystem identification

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Area of Science:

  • Cyber-Physical Systems Security
  • Industrial Control Systems
  • Networked Control Systems (NCS)

Background:

  • Networked Control Systems (NCS) offer significant advantages in Industry 4.0, including enhanced management and cost reduction.
  • However, NCS are vulnerable to cyber threats, particularly data injection attacks targeting sensor and controller communication links.
  • These attacks can compromise the integrity of physical plant operations.

Purpose of the Study:

  • To propose a link monitoring strategy for detecting linear time-invariant (LTI) functions used in data injection attacks within NCS.
  • To develop a bio-inspired countermeasure utilizing the Backtracking Search Optimization Algorithm (BSA).
  • To enhance detection accuracy through the novel Noise Impulse Integration (NII) technique.

Main Methods:

  • Implementation of a link monitoring strategy based on the Backtracking Search Optimization Algorithm (BSA).
  • Utilization of white Gaussian noise to excite potential attack functions.
  • Development and application of the Noise Impulse Integration (NII) technique, inspired by radar pulse integration.

Main Results:

  • The proposed countermeasure successfully and accurately identifies LTI functions executed during data injection attacks.
  • The system demonstrates no interference with normal NCS operations when no attack is present.
  • The Noise Impulse Integration (NII) technique significantly improves the accuracy of attack identification.

Conclusions:

  • The developed strategy provides an effective defense against data injection attacks in NCS.
  • The BSA and NII combination offers a robust solution for securing Industry 4.0 environments.
  • Accurate detection of cyber threats is crucial for maintaining the integrity and safety of industrial processes.