An Evaluation method for C2 Cyber-Physical Systems Reliability Based on Deep Learning

Abstract

As the battle space for Command and Control (C2) has grown more complex, the C2 reliability that threatens their ability is facing many new challenges. The Cyber-Physical System (CPS) technology is brought into C2 systems, C2 CPS architecture is structured, and a real-time online method for evaluating the reliability of C2 CPS is designed. The method establishes an assessment framework with use of deep learning, implements an online rank algorithm, and achieves the online analysis and evaluation of the reliability of the C2 CPS. The simulation experiments show the validity and correctness of the assessment method is verified. The system reliability has been greatly improved.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2014
Accession Number
ADA607655

Entities

People

  • Kai Kang
  • Ming He
  • Qingbing Zou
  • Xiliang Chen

Tags

Communities of Interest

  • C4I
  • Cyber
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Command And Control
  • Command And Control Systems
  • Computer Science
  • Control Systems
  • Deep Learning
  • Delphi Method
  • Electronic Equipment
  • Information Science
  • Information Systems
  • Learning
  • Machine Learning
  • Neural Networks
  • Reliability
  • Simulations
  • Test And Evaluation

Fields of Study

  • Computer science
  • Engineering

Readers

  • Joint Military Operations and Doctrine.
  • Regression Analysis.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks
  • Cyber
  • Cyber - Cryptography
  • Fully Networked C3
  • Fully Networked C3 - Command and Control
  • Space