Table of Content

Artificial Intelligence Empowered Blockchain Emerging Trends, Challenges, and Research Opportunities

Submission Deadline: 30 June 2022 (closed)

Guest Editors

Dr. Tariq Ahamed Ahanger, Prince Sattam Bin Abdulaziz University, Saudi Arabia.
Dr. Dr. Ashish Khanna, Maharaja Agrasen Institute of Technology (GGSIPU), India.
Dr. Abdullah Alqahtani, Prince Sattam Bin Abdulaziz University, Saudi Arabia.


Artificial Intelligence (AI) enables efficient computing for a variety of challenging computer science issues. With the introduction of blockchains, processing and storage are decentralized across edge devices, obviating the requirement for data to be collected and sent to a central server or the cloud. Deep learning algorithms require a significant enormous data quantity for training and testing. However, this results in privacy violations and a loss of data management for end-users. Distributing AI algorithm computation on a blockchain, as well as computing AI algorithms on blockchains via smart contracts, is a revolutionary paradigm. Federated learning is another distributed computing paradigm that allows for privacy-preserving machine learning. Integrating federated learning with blockchains gives distributed data processing and storage more privacy. Furthermore, AI algorithms may be used to improve the functioning of blockchains, such as by developing more efficient consensus algorithms and ensuring blockchain stability. Price volatility and fraud in cryptocurrencies may also be addressed using AI-based solutions. The blockchains can also aid with distributed AI security by providing immutability and integrity protection, allowing for more secure and privacy-preserving AI frameworks.

This special issue invites researchers, and authors to contribute original research, case studies, and reviews to incorporate IoT technology in synergy with advanced artificial intelligence techniques of the machine and deep learning techniques.


The following are some of the themes covered in this special edition (not limited to).

• Blockchain‐based on AI Techniques
• AI algorithms for smart contracts-based security
• Hybridization of federated learning and blockchains
• Blockchain‐based digital assets protection: Cost-Benefit Analysis
• Blockchain‐based digital assets protection: Fraud Detection
• Optimization in Blockchain‐based digital assets protection
• Reliability of blockchains based on Machine/Deep Learning
• Blockchains for secure decentralized Internet of Things Environment

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