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.
Summary
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.
Keywords
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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