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Security Framework for Network-Based Manufacturing Systems with Personalized Customization: An Industry 4.0 Approachoa mark
  • Hammad, Muhammad ;
  • Jillani, Rashad Maqbool ;
  • Ullah, Sami ;
  • Namoun, Abdallah ;
  • Tufail, Ali ;
  • Kim, Ki Hyung ;
  • Shah, Habib
Citations

SCOPUS

23

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Publication Year
2023-09-01
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Citation
Sensors, Vol.23
Keyword
Industry 4.0mobile industrial robotsnetwork-based manufacturing systemnewly personalized customization factoryNTRUEncrypt cryptographysecuritysmart manufacturing
Mesh Keyword
Advanced technologyCustomisationNetwork-basedNetwork-based manufacturing systemNewly personalized customization factoryNtruencrypt cryptographyOperational efficienciesProduction processSecuritySmart manufacturing
All Science Classification Codes (ASJC)
Analytical ChemistryInformation SystemsAtomic and Molecular Physics, and OpticsBiochemistryInstrumentationElectrical and Electronic Engineering
Abstract
Smart manufacturing is pivotal in the context of Industry 4.0, as it integrates advanced technologies like the Internet of Things (IoT) and automation to streamline production processes and improve product quality, paving the way for a competitive industrial landscape. Machines have become network-based through the IoT, where integrated and collaborated manufacturing system responds in real time to meet demand fluctuations for personalized customization. Within the network-based manufacturing system (NBMS), mobile industrial robots (MiRs) are vital in increasing operational efficiency, adaptability, and productivity. However, with the advent of IoT-enabled manufacturing systems, security has become a serious challenge because of the communication of various devices acting as mobile nodes. This paper proposes the framework for a newly personalized customization factory, considering all the advanced technologies and tools used throughout the production process. To encounter the security concern, an IoT-enabled NBMS is selected as the system model to tackle a black hole attack (BHA) using the NTRUEncrypt cryptography and the ad hoc on-demand distance-vector (AODV) routing protocol. NTRUEncrypt performs encryption and decryption while sending and receiving messages. The proposed technique is simulated by network simulator NS-2.35, and its performance is evaluated for different network environments, such as a healthy network, a malicious network, and an NTRUEncrypt-secured network based on different evaluation metrics, including throughput, goodput, end-to-end delay, and packet delivery ratio. The results show that the proposed scheme performs safely in the presence of a malicious node. The implications of this study are beneficial for manufacturing industries looking to embrace IoT-enabled subtractive and additive manufacturing facilitated by mobile industrial robots. Implementation of the proposed scheme ensures operational efficiency, enables personalized customization, and protects confidential data and communication in the manufacturing ecosystem.
ISSN
1424-8220
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/33646
DOI
https://doi.org/10.3390/s23177555
Fulltext

Type
Article
Funding
This research was partially supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP2021-2021-0-01835) and the research grant (No. 2021-0-00590 Decentralized High-Performance: 2021-0-00590; IITP2021-2021-0-01835). This research was also partially supported by KIAT (Korea Institute for Advancement of Technology) grant funded by the Korea Government (MOTIE) (P0008703, The Competency Development Program for Industry Specialist) and the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2021R1F1A1045861).The authors also extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Research Project under grant number RGP. 2/312/44.
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