References
- S. Choudhary and G. Meena, “Internet of Things: Protocols, Applications and Security Issues,” Procedia Computer Science, vol. 215, pp. 274–288, 2022, doi: 10.1016/j.procs.2022.12.030.
- A. Miglani and N. Kumar, “Blockchain management and machine learning adaptation for IoT environment in 5G and beyond networks: A systematic review,” Computer Communications, vol. 178, no. July 2021, pp. 37–63, 2021, doi: 10.1016/j.comcom.2021.07.009.
- P. Bothra, R. Karmakar, S. Bhattacharya, and S. De, “How can applications of blockchain and artificial intelligence improve performance of Internet of Things? – A survey,” Computer Networks, vol. 224, no. May 2021, p. 109634, 2023, doi: 10.1016/j.comnet.2023.109634.
- V. V Prabhakar, C. S. Belarmin Xavier, and K. M. Abubeker, “A Review on Challenges and Solutions in the Implementation of Ai, IoT and Blockchain in Construction Industry,” Materials Today: Proceedings, 2023, doi: 10.1016/j.matpr.2023.03.535.
- S. Singh, P. K. Sharma, B. Yoon, M. Shojafar, G. H. Cho, and I. H. Ra, “Convergence of blockchain and artificial intelligence in IoT network for the sustainable smart city,” Sustainable Cities and Society, vol. 63, no. April, 2020, doi: 10.1016/j.scs.2020.102364.
- A. Kumari, R. Gupta, and S. Tanwar, “Amalgamation of blockchain and IoT for smart cities underlying 6G communication: A comprehensive review,” Computer Communications, vol. 172, no. October 2020, pp. 102–118, 2021, doi: 10.1016/j.comcom.2021.03.005.
- E. Fazel, M. Z. Nezhad, J. Rezazadeh, M. Moradi, and J. Ayoade, “IoT convergence with machine learning & blockchain: A review,” Internet of Things (Netherlands), vol. 26, no. December 2023, p. 101187, 2024, doi: 10.1016/j.iot.2024.101187.
- N. S. Al-Blihed, N. F. Al-Mufadi, N. T. Al-Harbi, I. A. Al-Omari, and M. A. Al-Hagery, “Blockchain and machine learning in the internet of things: a review of smart healthcare,” IAES International Journal of Artificial Intelligence, vol. 12, no. 3, pp. 995–1006, 2023, doi: 10.11591/ijai.v12.i3.pp995-1006.
- B. K. Mohanta, D. Jena, U. Satapathy, and S. Patnaik, “Survey on IoT security: Challenges and solution using machine learning, artificial intelligence and blockchain technology,” Internet of Things (Netherlands), vol. 11, p. 100227, 2020, doi: 10.1016/j.iot.2020.100227.
- T. Nguyen, H. Nguyen, and T. Nguyen Gia, “Exploring the integration of edge computing and blockchain IoT: Principles, architectures, security, and applications,” Journal of Network and Computer Applications, vol. 226, no. September 2023, p. 103884, 2024, doi: 10.1016/j.jnca.2024.103884.
- A. M. Shamsan Saleh, “Blockchain for secure and decentralized artificial intelligence in cybersecurity: A comprehensive review,” Blockchain: Research and Applications, p. 100193, 2024, doi: 10.1016/j.bcra.2024.100193.
- P. Pandurangan et al., “Integrating cutting-edge technologies: AI, IoT, blockchain and nanotechnology for enhanced diagnosis and treatment of colorectal cancer - A review,” Journal of Drug Delivery Science and Technology, vol. 91, no. August 2023, p. 105197, 2024, doi: 10.1016/j.jddst.2023.105197.
- Z. Kamal, M. Lachgar, and H. Hrimech, “Blockchain, IoT and AI in logistics and transportation : A systematic review,” Transport Economics and Management, vol. 2, no. July, pp. 275–285, 2024, doi: 10.1016/j.team.2024.09.002.
- M. Gupta, M. Kumar, and R. Dhir, “Unleashing the prospective of blockchain-federated learning fusion for IoT security: A comprehensive review,” Computer Science Review, vol. 54, no. June, p. 100685, 2024, doi: 10.1016/j.cosrev.2024.100685.
- S. Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System,” vol. 15, no. 4, pp. 580–596, 2008.
- M. Pasqua, A. Benini, F. Contro, M. Crosara, and M. D. Preda, “Enhancing Ethereum smart-contracts static analysis by computing a precise Control-Flow Graph of Ethereum bytecode ☆,” The Journal of Systems & Software, vol. 200, p. 111653, 2023, doi: 10.1016/j.jss.2023.111653.
- T. Guimarãesa et al., “Blockchain Analytics - Real-time Log Management in Healthcare Blockchain Analytics - Real-time Log Management in Healthcare,” vol. 00, 2022, doi: 10.1016/j.procs.2022.03.094.
- B. Bhushan, A. Khamparia, K. M. Sagayam, S. K. Sharma, M. A. Ahad, and N. C. Debnath, “Blockchain for smart cities: A review of architectures, integration trends and future research directions,” Sustainable Cities and Society, vol. 61, no. March, p. 102360, 2020, doi: 10.1016/j.scs.2020.102360.
- Y. Shen and X. Zhang, “Factors influencing blockchain adoption in supply chain management practices: A study based on the oil industry,” Journal of Innovation & Knowledge, vol. 8, no. 3, p. 100384, 2023, [Online]. Available: DOI: 10.1016/j.jik.2023.100384.
- G. Tripathi, M. A. Ahad, and G. Casalino, “A comprehensive review of blockchain technology: Underlying principles and historical background with future challenges,” Decision Analytics Journal, vol. 9, no. March, p. 100344, 2023, doi: 10.1016/j.dajour.2023.100344.
- M. R. Islam, M. M. Rahman, M. Mahmud, M. A. Rahman, M. H. S. Mohamad, and A. H. Embong, “A Review on Blockchain Security Issues and Challenges,” 2021 IEEE 12th Control and System Graduate Research Colloquium, ICSGRC 2021 - Proceedings, no. August, pp. 227–232, 2021, doi: 10.1109/ICSGRC53186.2021.9515276.
- D. R. Kiran, “Chapter 35 - Internet of Things,” in Production Planning and Control, D. R. Kiran, Ed. Butterworth-Heinemann, 2019, pp. 495–513.
- E. Gelenbe, M. Nakıp, and T. Czachórski, “Improving Massive Access to IoT Gateways,” Performance Evaluation, vol. 157–158, p. 102308, 2022, doi: 10.1016/j.peva.2022.102308.
- C. K. Rath, A. K. Mandal, and A. Sarkar, “Microservice based scalable IoT architecture for device interoperability,” Computer Standards and Interfaces, vol. 84, no. October 2022, 2023, doi: 10.1016/j.csi.2022.103697.
- S. Rudrakar and P. Rughani, “IoT based Agriculture (Ag-IoT): A detailed study on Architecture, Security and Forensics,” Information Processing in Agriculture, no. August, 2023, doi: 10.1016/j.inpa.2023.09.002.
- L. Yang and A. Shami, “IoT data analytics in dynamic environments: From an automated machine learning perspective,” Engineering Applications of Artificial Intelligence, vol. 116, no. August, p. 105366, 2022, doi: 10.1016/j.engappai.2022.105366.
- P. Akhtar, Z. Khan, S. Tarba, and U. Jayawickrama, “The Internet of Things, dynamic data and information processing capabilities, and operational agility,” Technological Forecasting and Social Change, vol. 136, no. May 2017, pp. 307–316, 2018, doi: 10.1016/j.techfore.2017.04.023.
- I. H. Sarker, “Machine Learning: Algorithms, Real-World Applications and Research Directions,” SN Computer Science, vol. 2, no. 3, pp. 1–21, 2021, doi: 10.1007/s42979-021-00592-x.
- A. U. Osarogiagbon, F. Khan, R. Venkatesan, and P. Gillard, “Review and analysis of supervised machine learning algorithms for hazardous events in drilling operations,” Process Safety and Environmental Protection, vol. 147, pp. 367–384, 2021, doi: 10.1016/j.psep.2020.09.038.
- D. del-Pozo-Bueno, D. Kepaptsoglou, F. Peiró, and S. Estradé, “Comparative of machine learning classification strategies for electron energy loss spectroscopy: Support vector machines and artificial neural networks,” Ultramicroscopy, vol. 253, no. July, 2023, doi: 10.1016/j.ultramic.2023.113828.
- K. Hu et al., “A review of research on reinforcement learning algorithms for multi-agents,” Neurocomputing, vol. 599, no. November 2023, p. 128068, 2024, doi: 10.1016/j.neucom.2024.128068.
- N. S. A. Polireddi, “An effective role of artificial intelligence and machine learning in banking sector,” Measurement: Sensors, vol. 33, no. November 2023, p. 101135, 2024, doi: 10.1016/j.measen.2024.101135.
- B. Abdualgalil and S. Abraham, “Applications of Machine Learning Algorithms and Performance Comparison: A Review,” International Conference on Emerging Trends in Information Technology and Engineering, ic-ETITE 2020, pp. 1–6, 2020, doi: 10.1109/ic-ETITE47903.2020.490.
- D. D. Nguyen and M. I. Ali, “Enabling On-demand decentralized IoT collectability marketplace using blockchain and crowdsensing,” Global IoT Summit, GIoTS 2019 - Proceedings, pp. 1–6, 2019, doi: 10.1109/GIOTS.2019.8766346.
- C. Liu, Y. Xiao, V. Javangula, Q. Hu, S. Wang, and X. Cheng, “NormaChain: A blockchain-based normalized autonomous transaction settlement system for IoT-based e-commerce,” IEEE Internet of Things Journal, vol. 6, no. 3, pp. 4680–4693, 2019, doi: 10.1109/JIOT.2018.2877634.
- Q. Ren, K. L. Man, M. Li, and B. Gao, “Using Blockchain to Enhance and Optimize IoT-based Intelligent Traffic System,” 2019 International Conference on Platform Technology and Service, PlatCon 2019 - Proceedings, pp. 1–4, 2019, doi: 10.1109/PlatCon.2019.8669412.
- W. Liang, L. You, and G. Hu, “LRS_PKI: A novel blockchain-based PKI framework using linkable ring signatures,” Computer Networks, vol. 237, no. August, p. 110043, 2023, doi: 10.1016/j.comnet.2023.110043.
- S. Khanji, O. Alfandi, L. Ahmad, L. Kakkengal, and M. Al-kfairy, “A systematic analysis on the readiness of Blockchain integration in IoT forensics,” Forensic Science International: Digital Investigation, vol. 42–43, p. 301472, 2022, doi: 10.1016/j.fsidi.2022.301472.
- A. Tomar, N. Gupta, D. Rani, and S. Tripathi, “Blockchain-assisted authenticated key agreement scheme for IoT-based healthcare system,” Internet of Things (Netherlands), vol. 23, no. June, p. 100849, 2023, doi: 10.1016/j.iot.2023.100849.
- S. Brotsis et al., “Blockchain meets Internet of Things (IoT) forensics: A unified framework for IoT ecosystems,” Internet of Things (Netherlands), vol. 24, no. August, p. 100968, 2023, doi: 10.1016/j.iot.2023.100968.
- X. Lu, “Implementation of art therapy assisted by the internet of medical things based on blockchain and fuzzy set theory,” Information Sciences, vol. 632, no. March, pp. 776–790, 2023, doi: 10.1016/j.ins.2023.03.044.
- D. Kumar, R. K. Singh, R. Mishra, and T. U. Daim, “Roadmap for integrating blockchain with Internet of Things (IoT) for sustainable and secured operations in logistics and supply chains: Decision making framework with case illustration,” Technological Forecasting and Social Change, vol. 196, no. September, p. 122837, 2023, doi: 10.1016/j.techfore.2023.122837.
- H. Nguyen, D. Nawara, and R. Kashef, “Connecting the indispensable roles of IoT and artificial intelligence in smart cities: A survey,” Journal of Information and Intelligence, no. December 2023, pp. 1–25, 2024, doi: 10.1016/j.jiixd.2024.01.003.
- W. S. Costa et al., “Planning and resource allocation of a hybrid IoT network using artificial intelligence,” Internet of Things (Netherlands), vol. 26, no. April, p. 101225, 2024, doi: 10.1016/j.iot.2024.101225.
- K. Alpan, K. Tuncal, C. Ozkan, B. Sekeroglu, and Y. K. Ever, “Design and simulation of global model for carbon emission reduction using IoT and artificial intelligence,” Procedia Computer Science, vol. 204, pp. 627–634, 2022, doi: 10.1016/j.procs.2022.08.076.
- A. A. Malibari, “An efficient IoT-Artificial intelligence-based disease prediction using lightweight CNN in healthcare system,” Measurement: Sensors, vol. 26, no. October 2022, p. 100695, 2023, doi: 10.1016/j.measen.2023.100695.
- F. Hussain, R. Hussain, S. A. Hassan, and E. Hossain, “Machine Learning in IoT Security: Current Solutions and Future Challenges,” IEEE Communications Surveys and Tutorials, vol. 22, no. 3, pp. 1686–1721, 2020, doi: 10.1109/COMST.2020.2986444.
- F. Alwahedi, A. Aldhaheri, M. A. Ferrag, A. Battah, and N. Tihanyi, “Machine learning techniques for IoT security: Current research and future vision with generative AI and large language models,” Internet of Things and Cyber-Physical Systems, vol. 4, no. August 2023, pp. 167–185, 2024, doi: 10.1016/j.iotcps.2023.12.003.
- T. Mazhar et al., “Analysis of IoT Security Challenges and Its Solutions Using Artificial Intelligence,” Brain Sciences, vol. 13, no. 4, 2023, doi: 10.3390/brainsci13040683.
- S. Vyas, M. Gupta, and R. Yadav, “Converging Blockchain and Machine Learning for Healthcare,” Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019, pp. 709–711, 2019, doi: 10.1109/AICAI.2019.8701230.
- P. Singh, Z. Elmi, Y. yip Lau, M. Borowska-Stefańska, S. Wiśniewski, and M. A. Dulebenets, “Blockchain and AI technology convergence: Applications in transportation systems,” Vehicular Communications, vol. 38, no. 2022, 2022, doi: 10.1016/j.vehcom.2022.100521.
- M. Soori, R. Dastres, and B. Arezoo, “AI-powered blockchain technology in industry 4.0, a review,” Journal of Economy and Technology, vol. 1, no. November 2023, pp. 222–241, 2023, doi: 10.1016/j.ject.2024.01.001.
- H. Y. Chen, K. Sharma, C. Sharma, and S. Sharma, “Integrating explainable artificial intelligence and blockchain to smart agriculture: Research prospects for decision making and improved security,” Smart Agricultural Technology, vol. 6, no. November, p. 100350, 2023, doi: 10.1016/j.atech.2023.100350.
- D. Bhumichai, C. Smiliotopoulos, R. Benton, G. Kambourakis, and D. Damopoulos, “The Convergence of Artificial Intelligence and Blockchain: The State of Play and the Road Ahead,” Information (Switzerland), vol. 15, no. 5, pp. 1–32, 2024, doi: 10.3390/info15050268.
- D. Ressi, R. Romanello, C. Piazza, and S. Rossi, “AI-enhanced blockchain technology: A review of advancements and opportunities,” Journal of Network and Computer Applications, vol. 225, no. May 2023, p. 103858, 2024, doi: 10.1016/j.jnca.2024.103858.
- O. Popoola, M. Rodrigues, J. Marchang, A. Shenfield, A. Ikpehia, and J. Popoola, “A critical literature review of security and privacy in smart home healthcare schemes adopting IoT & blockchain: Problems, Challenges and Solutions,” Blockchain: Research and Applications, vol. 5, no. 2, p. 100178, 2023, doi: 10.1016/j.bcra.2023.100178.
- P. Nath, J. R. Mushahary, U. Roy, M. Brahma, and P. K. Singh, “AI and Blockchain-based source code vulnerability detection and prevention system for multiparty software development,” Computers and Electrical Engineering, vol. 106, no. June 2022, p. 108607, 2023, doi: 10.1016/j.compeleceng.2023.108607.
- S. M. Alrubei, E. Ball, and J. M. Rigelsford, “A Secure Blockchain Platform for Supporting AI-Enabled IoT Applications at the Edge Layer,” IEEE Access, vol. 10, pp. 18583–18595, 2022, doi: 10.1109/ACCESS.2022.3151370.
- H. Hu, J. Xu, M. Liu, and M. K. Lim, “Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning,” Journal of Business Research, vol. 156, no. December 2022, p. 113480, 2023, doi: 10.1016/j.jbusres.2022.113480.
- S. K. Singh, S. Rathore, and J. H. Park, “BlockIoTIntelligence: A Blockchain-enabled Intelligent IoT Architecture with Artificial Intelligence,” Future Generation Computer Systems, vol. 110, pp. 721–743, 2020, doi: 10.1016/j.future.2019.09.002.
- M. Lei, L. Xu, T. Liu, S. Liu, and C. Sun, “Integration of Privacy Protection and Blockchain-Based Food Safety Traceability: Potential and Challenges,” Foods, vol. 11, no. 15, 2022, doi: 10.3390/foods11152262.
- N. Mangala et al., “Secure pharmaceutical supply chain using blockchain in IoT cloud systems,” Internet of Things (Netherlands), vol. 26, no. April, p. 101215, 2024, doi: 10.1016/j.iot.2024.101215.
- X. Feng, J. Wu, Y. Wu, J. Li, and W. Yang, “Blockchain and digital twin empowered trustworthy self-healing for edge-AI enabled industrial Internet of things,” Information Sciences, vol. 642, no. May, p. 119169, 2023, doi: 10.1016/j.ins.2023.119169.
- W. Moulahi, I. Jdey, T. Moulahi, M. Alawida, and A. Alabdulatif, “A blockchain-based federated learning mechanism for privacy preservation of healthcare IoT data,” Computers in Biology and Medicine, vol. 167, no. June, p. 107630, 2023, doi: 10.1016/j.compbiomed.2023.107630.
- J. Wang, H. Jin, J. Chen, J. Tan, and K. Zhong, “Anomaly detection in Internet of medical Things with Blockchain from the perspective of deep neural network,” Information Sciences, vol. 617, pp. 133–149, 2022, doi: 10.1016/j.ins.2022.10.060.
- Y. D. Al-Otaibi, “K-nearest neighbour-based smart contract for internet of medical things security using blockchain,” Computers and Electrical Engineering, vol. 101, no. May, p. 108129, 2022, doi: 10.1016/j.compeleceng.2022.108129.
- A. Zekiye and Ö. Özkasap, “Decentralized Healthcare Systems with Federated Learning and Blockchain,” 2023, [Online]. Available:
http://arxiv.org/abs/2306.17188 . - I. Ahmed, Y. Zhang, G. Jeon, W. Lin, M. R. Khosravi, and L. Qi, “A blockchain- and artificial intelligence-enabled smart IoT framework for sustainable city,” International Journal of Intelligent Systems, vol. 37, no. 9, pp. 6493–6507, 2022, doi: 10.1002/int.22852.
- A. Shankar and C. Maple, “Securing the Internet of Things-enabled smart city infrastructure using a hybrid framework,” Computer Communications, vol. 205, no. August 2022, pp. 127–135, 2023, doi: 10.1016/j.comcom.2023.04.008.
- A. Kumari, R. Gupta, S. Tanwar, and N. Kumar, “Blockchain and AI amalgamation for energy cloud management: Challenges, solutions, and future directions,” Journal of Parallel and Distributed Computing, vol. 143, pp. 148–166, 2020, doi: 10.1016/j.jpdc.2020.05.004.