Smart City Gnosys

Smart city article details

Title	Deepblockscheme: A Deep Learning-Based Blockchain Driven Scheme For Secure Smart City
ID_Doc	18120
Authors	Singh, SK; El Azzaoui, A; Kim, TW; Pan, Y; Park, JH
Year	2021
Published	HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES, 11
DOI	http://dx.doi.org/10.22967/HCIS.2021.11.012
Abstract	Today, the continuous deployment of sensors and the Internet of Things (IoT) has boosted the amount of manufacturing data in the smart city. Factories are rapidly becoming more interconnected in the world with sensing data. Big data are generally characterized by five V's: high volume, high value, high veracity, high variety, and high velocity. Latency, scalability, centralization, reliability, security, and privacy are the major challenges for advanced smart city applications such as smart manufacturing, smart factory, and others. Meanwhile, blockchain is an emerging distributed technology that is deployed to minimize central authority control and provide a secure environment in the recent applications above. On the other hand, deep learning is one of the leading-edge technologies that offer modern analytic tools for the processing and analysis of data and provide scalable production in the smart factory application in a smart city. In this paper, we propose DeepBlockScheme: A Deep Learning-based Blockchain Driven Scheme for a Secure Smart City, where blockchain is used in a distributed manner at the fog layer to ensure the integrity, decentralization, and security of manufacturing data. Deep learning is utilized at the cloud layer to increase production, automate data analysis, and increase the communication bandwidth of the smart factory and smart manufacturing applications in smart cities. We present a case study of car manufacturing with the latest service scenarios for the proposed scheme and compare it to existing research studies using crucial parameters such as security and privacy tools. Finally, open research challenges are also discussed based on the proposed scheme.
Author Keywords	Deep Learning; Blockchain; Smart Manufacturing; Scalability; Security and Privacy

Similar Articles

Id	Similarity	Authors	Title	Published
12370	0.886	Mishra S.; Chaurasiya V.K.	Blockchain And Iot Based Infrastructure For Secure Smart City Using Deep Learning Algorithm With Dingo Optimization	Wireless Personal Communications, 132, 1 (2023)
8312	0.884	Lanjewar U.; Khekare G.; Wahi A.	An In-Depth Review Of Machine Learning, Blockchain, And Deep Learning Models For Intelligent Security And Resilience Enhancement In Smart Cities	2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024 - Proceedings (2024)
59642	0.884	Aravinth S.S.	Unleashing The Power Of Data And Security By Integrating Deep Learning And Blockchain In Smart City Infrastructure Development - A Future Perspective	Deep Learning and Blockchain Technology for Smart and Sustainable Cities (2025)
490	0.879	Ahmed I.; Zhang Y.; Jeon G.; Lin W.; Khosravi M.R.; Qi L.	A Blockchain- And Artificial Intelligence-Enabled Smart Iot Framework For Sustainable City	International Journal of Intelligent Systems, 37, 9 (2022)
7407	0.878	Kumar A.; Kumar S.	An Advance Encryption And Attack Detection Framework For Securing Smart Cities Data In Blockchain Using Deep Learning Approach	Wireless Personal Communications, 135, 3 (2024)
17804	0.878	Subramaniyaswamy V.; Revathy G.; Ravi L.; Thillaiarasu N.; Kshetri N.	Deep Learning And Blockchain Technology For Smart And Sustainable Cities	Deep Learning and Blockchain Technology for Smart and Sustainable Cities (2025)
25749	0.877	Revathy G.; Indhumathi R.; Jebaseeli A.N.; Fairosebanu A.; Aurchana P.; Sreedevi B.	Exploring The Potential Of Blockchain And Deep Learning In Smart City Applications	Deep Learning and Blockchain Technology for Smart and Sustainable Cities (2025)
4517	0.876	Mathalai Raj J.; Siva Ranjani S.	A Secured Blockchain Method For Multivariate Industrial Iot-Oriented Infrastructure Based On Deep Residual Squeeze And Excitation Network With Single Candidate Optimizer	Internet of Things (Netherlands), 22 (2023)
35041	0.869	Moawad M.M.; Madbouly M.M.; Guirguis S.K.	Leveraging Blockchain And Machine Learning To Improve Iot Security For Smart Cities	Lecture Notes on Data Engineering and Communications Technologies, 164 (2023)
35956	0.869	Dritsas E.; Trigka M.	Machine Learning For Blockchain And Iot Systems In Smart Cities: A Survey	Future Internet, 16, 9 (2024)