A Blockchain Security Based IoT-Enabled System for Safe and Effective Logistics Management in IR 4.0
Keywords:
Blockchain, Security, IoT, Logistics, , IR 4.0Abstract
As a result of the revolution brought on by industrial 4.0, the global logistics industry is growing at a rapid rate. Concurrently, logistics operations are undergoing constant change as new technologies such as the internet of things (IoT), cloud computing, and big data are implemented. These Internet of Things devices enhance the functionality of the logistics function by enhancing real-time product tracking, improving data collection, and intelligently storing logistics data, among other things. Because of the centralised database structure of these logistics systems, certain of these new technologies open the door to the possibility of cyberattacks on these systems. The parties involved in the logistics operations must communicate with one another in order to share confidential information about customers and details about products. This is due to the fact that so many logistics stakeholders are being engaged in the process. It is vulnerable to unauthorised access, which may result in fraudulent activity or the production of counterfeit goods by a malicious actor operating within the system. All of these challenges are significant because maintaining the integrity of the logistics data is essential to providing good service to customers. The application of Blockchain's special features, such as immutability, efficient cryptography, and a distributed decentralised storage system, will be used to address these challenges once it is deployed as an innovation. In conclusion, Blockchain has the potential to improve operational efficiency while also ensuring the safety of the data involved in the logistics process. According to the findings of the study, the technologies underlying Industry 4.0 have the potential to make supply chains more agile, transparent, and resilient. In addition, the study demonstrates that despite the fact that the advantages of integrating technologies related to Industry 4.0 into supply chains are widely acknowledged, there is still a dearth of applications, related research, and actual-world use cases. Nevertheless, it is abundantly clear that companies that do not adopt the technologies will eventually go out of business. In the event that the pandemic has revealed bottlenecks in the practises we use for our supply chain, the solution is to integrate advanced technologies from Industry 4.0.
Downloads
References
Aslan, E. How Supply Chain Management Will Change in the Industry 4.0 Era? In Research Anthology on Cross-Industry Challenges of Industry 4.0; Information Resources Management Association, IGI Global: Hershey, PA, USA, 2021; pp. 1015–1035.
Abubakar, A.I.; Omeke, K.G.; Ozturk, M.; Hussain, S.; Imran, M.A. The role of artificial intelligence driven 5G networks in COVID-19 outbreak: Opportunities, challenges, and future outlook. Front. Commun. Netw. 2020, 1, 4.
Attique, M.; Farooq, M.S.; Khelifi, A.; Abid, A. Prediction of Therapeutic Peptides Using Machine Learning: Computational Models, Datasets, and Feature Encodings. IEEE Access 2020, 8, 148570–148594.
Panarello, N. Tapas, G. Merlino, and F. Longo, “Blockchain and IoT integration: a systematic survey,” Sensors, vol. 18, p. 2575, 2018.
Awan, M.J.; Yasin, A.; Nobanee, H.; Ali, A.A.; Shahzad, Z.; Nabeel, M.; Zain, A.M.; Shahzad, H.M.F. Fake News Data Exploration and Analytics. Electronics 2021, 10, 2326.
Awan, M.; Rahim, M.; Salim, N.; Ismail, A.; Shabbir, H. Acceleration of knee MRI cancellous bone classification on google colaboratory using convolutional neural network. Int. J. Adv. Trends Comput. Sci. 2019, 8, 83–88.
Awan, M.J.; Rahim, M.S.M.; Nobanee, H.; Yasin, A.; Khalaf, O.I.; Ishfaq, U. A Big Data Approach to Black Friday Sales. Intell. Autom. Soft Comput. 2021, 27, 785–797.
Awan, M.J.; Raza, A.; Yasin, A.; Shehzad, H.M.F.; Butt, I. The Customized Convolutional Neural Network of Face Emotion Expression Classification. Ann. Rom. Soc. Cell Biol. 2021, 25, 5296–5304.
Bucea-Manea-T, oni¸s, R.; Martins, O.M.D.; Bucea-Manea-T, oni¸s, R.; Gheorghit,ă, C.; Kuleto, V.; Ili´c, M.P.; Simion, V.-E. Blockchain Technology Enhances Sustainable Higher Education. Sustainability 2021, 13, 12347.
C.-C. Lin and J. W. Yang, “Cost-efficient deployment of fog computing systems at logistics centers in industry 4.0,” IEEE Transactions on Industrial Informatics, vol. 14, no. 10, pp. 4603–4611, 2018.
Childerhouse, P.; Hermiz, R.; Mason-Jones, R.; Popp, A.; Towill, D.R. Information flow in automotive supply chains–present industrial practice. Ind. Manag. Data Syst. 2003, 103, 491–502.
Cole, R.; Stevenson, M.; Aitken, J. Blockchain technology: Implications for operations and supply chain management. Supply Chain Manag. Int. J. 2019, 24, 469–483.
Bitcoin, “A peer-to-peer electronic cash system,” 2020, https:// bitcoin.org/bitcoin.pdf.
Fatima, A. (2021). Drivers in the Adoption of Blockchain Technology in the Select Services Sector of India. Kaav International Journal of Economics, Commerce & Business Management, 8(2), 28https://doi.org/10.52458/23484969.2021.v8.iss2.kp.a7
F. Casino, L. Azpilicueta, P. Lopez-Iturri, E. Aguirre, F. Falcone, and A. Solanas, “Optimized wireless channel characterization in large complex environments by hybrid ray launching-collaborative filtering approach,” IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 780–783, 2017.
Geodis. A White Paper on Supply Chain Worldwide Survey. 2017.
G. Perboli, S. Musso, and M. Rosano, “Blockchain in logistics and supply chain: a lean approach for designing real-world use cases,” IEEE Access, vol. 6, pp. 62018–62028, 2018.
Iqbal, S.; Hussain, M.; Munir, M.U.; Hussain, Z.; Mehrban, S.; Ashraf, M.A. Crypto-Currency: Future of FinTech. In Research Anthology on Blockchain Technology in Business, Healthcare, Education, and Government; IGI Global: Hershey, PA, USA, 2021; pp. 1915–1924.
Ignaciuk, P.; Wieczorek, Ł. Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning. Appl. Sci. 2020, 10, 7851.
Jain, S. K., & N. (2019). Comprehensive Review of Smart Home Systems Using IoT. Kaav International Journal of Science, Engineering & Technology, 6(4), 13-16. https://doi.org/10.52458/23485477.2019.v6.iss4.kp.a3
L. (2022). A Review on the IOT System. Kaav International Journal of Science, Engineering & Technology, 9(1), 1-12. https://doi.org/10.52458/23485477.2022.v9.iss1.kp.a1
Lu, D.; Moreno-Sanchez, P.; Mitra, P.; Feldman, K.; Fodale, J.; Kosofsky, J.; Kate, A. Toward Privacy-Aware Traceability for Automotive Supply Chains. SAE Int. J. Transp. Cybersecur. Priv. 2021, 4.
Lohmer, J.; Lasch, R. Blockchain in operations management and manufacturing: Potential and barriers. Comput. Ind. Eng. 2020, 149, 106789.
Mastos, T.D.; Nizamis, A.; Terzi, S.; Gkortzis, D.; Papadopoulos, A.; Tsagkalidis, N.; Ioannidis, D.; Votis, K.; Tzovaras, D. Introducing an application of an industry 4.0 solution for circular supply chain management. J. Clean. Prod. 2021, 300, 126886.
Mylrea, M.; Gourisetti, S.N.G. Blockchain for supply chain cybersecurity, optimization and compliance. In Proceedings of the 2018 Resilience Week (RWS), Denver, CO, USA, 20–23 August 2018; pp. 70–76.
Mujahid, A.; Awan, M.; Yasin, A.; Mohammed, M.; Damaševiˇcius, R.; Maskeliunas, R.; Abdulkareem, K. Real-Time Hand Gesture ¯ Recognition Based on Deep Learning YOLOv3 Model. Appl. Sci. 2021, 11, 4164.
Negka, L.; Gketsios, G.; Anagnostopoulos, N.A.; Spathoulas, G.; Kakarountas, A.; Katzenbeisser, S. Employing blockchain and physical unclonable functions for counterfeit IoT devices detection. In Proceedings of the International Conference on Omni-Layer Intelligent Systems, Crete, Greece, 5–7 May 2019; pp. 172–178.
Nadeem, M.W.; Al Ghamdi, M.A.; Hussain, M.; Khan, M.A.; Khan, K.M.; AlMotiri, S.H.; Butt, S.A. Brain Tumor Analysis Empowered with Deep Learning: A Review, Taxonomy, and Future Challenges. Brain Sci. 2020, 10, 118.
N. Zhang, “Smart Logistics Path for Cyber-Physical Systems With the Internet of Things,” IEEE Access, vol. 6, pp. 70808– 70819, 2018.
Pervez, H.; Haq, I.U. Blockchain and IoT based disruption in logistics. In Proceedings of the 2nd International Conference on Communication, Computing and Digital Systems (C-CODE), Islamabad, Pakistan, 6–7 March 2019; pp. 276–281.
Punathumkandi, S.; Sundaram, V.M.; Panneer, P. Interoperable Permissioned-Blockchain with Sustainable Performance. Sustainability 2021, 13, 11132.
Pundir, A.K.; Jagannath, J.D.; Chakraborty, M.; Ganpathy, L. Technology Integration for Improved Performance: A Case Study in Digitization of Supply Chain with Integration of Internet of Things and Blockchain Technology. In Proceedings of the 9th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 7–9 January 2019; pp. 0170–0176.
Raja Santhi, A.; Muthuswamy, P. Influence of Blockchain Technology in Manufacturing Supply Chain and Logistics. Logistics 2022, 6, 15.
R. P. Sarode, “Blockchain for committing peer-to-peer transactions using distributed ledger technologies,” Journal of Computational Science and Engineering, vol. 1, no. 1, p. 1, 2008.
S. Wang, D. Li, Y. Zhang, and J. Chen, “Smart contract-based product traceability system in the supply chain scenario,” IEEE Access, vol. 7, pp. 115 122–115 133, 2019.
Tan, B.Q.; Wang, F.; Liu, J.; Kang, K.; Costa, F. A Blockchain-Based Framework for Green Logistics in Supply Chains. Sustainability 2020, 12, 4656.
Tory, “Blockchain in Healthcare Today Best Article Award 2020,” Blockchain in Healthcare Today, 2022.
Tapscott and D. Tapscott, “How blockchain is changing finance,” 2017, https://www.bedicon.org/wpcontent/uploads/ 2018/01/financetopic2source2:pdf.
V. Di and A. Varriale, “Blockchain technology in supply chain management for sustainable performance: evidence from the airport industry,” International Journal of Information Management, vol. 52, article 102014, 2020.
W. Kersten, M. Seiter, B. von See, N. Hackius, and T. Maurer, Logistics and Supply Chain Management Trends and Strategies–Digital Transformation Opportunities, DVV Media Group, Hamburg, Germany, 2017.
Wang, Z.; Wang, T.; Hu, H.; Gong, J.; Ren, X.; Xiao, Q. Blockchain-based framework for improving supply chain traceability and information sharing in precast construction. Autom. Constr. 2019, 111, 103063.
U. Nwosu and S. B. Goyal, “Blockchain Transforming Cyber-Attacks: Healthcare Industry,” in Innovations in BioInspired Computing and Applications. IBICA 2020, A. Abraham, H. Sasaki, R. Rios, N. Gandhi, U. Singh, and K. Ma, Eds., vol. 1372 of Advances in Intelligent Systems and Computing, pp. 258–266, Springer, Cham, 2020.
Yaga, D.; Mell, P.; Roby, N.; Scarfone, K. Blockchain technology overview. arXiv 2019, arXiv:1906.11078.
Y. Ding, M. Jin, S. Li, and D. Feng, “Smart logistics based on the internet of things technology: an overview,” International Journal of Logistics Research and Applications, vol. 24, no. 4, pp. 323–345, 2021.
Y. Zhang, Z. Guo, J. Lv, and Y. Liu, “A Framework for Smart Production-Logistics Systems Based on CPS and Industrial IoT,” IEEE Transactions on Industrial Informatics, vol. 14, no. 9, pp. 4019–4032, 2018.
Y. G. Fu and J. Zhu, “Operation mechanisms for intelligent logistics system: a blockchain perspective,” IEEE Access, vol. 7, pp. 144202–144213, 2019.
file:///C:/Users/vikagar/Downloads/Blockchain_Based_IoT_Devices_in_Supply_C.pdf
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
