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Security Framework for Network-Based Manufacturing Systems with Personalized Customization: An Industry 4.0 Approach.

Muhammad Hammad1, Rashad Maqbool Jillani2, Sami Ullah3

  • 1Faculty of Mechanical Engineering, GIK Institute of Engineering Sciences and Technology, Topi 23640, Pakistan.

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|September 9, 2023
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Summary
This summary is machine-generated.

This study introduces a secure framework for smart manufacturing using the Internet of Things (IoT) and mobile industrial robots (MiRs). It effectively prevents black hole attacks (BHAs) in network-based manufacturing systems (NBMS), ensuring data security and operational efficiency.

Keywords:
Industry 4.0NTRUEncrypt cryptographymobile industrial robotsnetwork-based manufacturing systemnewly personalized customization factorysecuritysmart manufacturing

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Area of Science:

  • Smart Manufacturing
  • Industry 4.0
  • Cybersecurity in Industrial IoT

Background:

  • Smart manufacturing, driven by Industry 4.0, leverages IoT and automation for efficient production.
  • Network-based manufacturing systems (NBMS) with mobile industrial robots (MiRs) enhance adaptability but face security challenges.
  • The proliferation of connected devices in IoT-enabled manufacturing creates vulnerabilities, particularly to attacks like the black hole attack (BHA).

Purpose of the Study:

  • To propose a novel framework for a personalized customization factory within the Industry 4.0 paradigm.
  • To address the critical security challenge of black hole attacks (BHAs) in IoT-enabled NBMS.
  • To enhance the security and efficiency of manufacturing systems utilizing mobile industrial robots (MiRs).

Main Methods:

  • Developed a framework for a personalized customization factory integrating advanced manufacturing technologies.
  • Implemented a security solution for IoT-enabled NBMS using NTRUEncrypt cryptography and the Ad hoc On-Demand Distance-Vector (AODV) routing protocol.
  • Simulated the proposed technique using Network Simulator NS-2.35, evaluating performance in healthy, malicious, and secured network environments.

Main Results:

  • The proposed NTRUEncrypt and AODV-based scheme effectively mitigates black hole attacks (BHAs) in the simulated IoT-enabled NBMS.
  • Performance evaluation demonstrated the scheme's safety and efficacy in the presence of malicious nodes.
  • Key performance metrics such as throughput, goodput, end-to-end delay, and packet delivery ratio were analyzed.

Conclusions:

  • The developed framework ensures operational efficiency and enables personalized customization in smart manufacturing.
  • The proposed security mechanism protects confidential data and communication within the manufacturing ecosystem.
  • This study provides a valuable contribution for industries adopting IoT-enabled manufacturing and mobile industrial robots (MiRs).