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Applications of Blockchain, Machine Learning and Deep Learning in Data Security

Submission Deadline: 30 April 2021 (closed)

Guest Editors

Dr. Mangesh M. Ghonge, Sandip Institute of Technology and Research Center, India.
Dr. Ramchandra Mangrulkar, SVKM’s Dwarkadas J. Sanghvi College of Engineering, India.
Dr. Pradip M Jawandhiya, Pankaj Laddhad Institute of Technology & Management Studies, India.


Blockchain, machine learning, and deep learning are gaining fast traction and thrust around the world. Blockchain is an evolving technology that is widely based across many countries and communities, with the ability to challenge any industry's conventional models. The decentralized system of blockchain technology is in contrast to the centralized systems of operation in use today.

The blockchain technology uses a type of decentralized architecture of the database, in which the monitoring and authentication of such activities rely on the agreement of many parties rather than a single authority. It makes the blockchain technology safer, faster, and more accessible for everyone compared to the centralized technologies. However, the applications for blockchain technology are not only limited to the financial sector but can also be applied to other areas such as smart city, healthcare, food and logistics, security, manufacturing automation, energy, and utilities, etc.

On the other hand, with predictive and descriptive algorithms, machine learning, and deep learning, making huge waves in harnessing existing data to identify patterns and gain insights. Data scientists have long struggled to maintain the accuracy of machine learning and deep learning dataset. Datasets can be very costly to obtain, as it is difficult to build and preserve the quality of a dataset, depending on both the correct selection of the elements and the homogeneity of the data found within. As a highly secure storage medium, blockchain offers a technical quantum leap in keeping data integrity. Besides, the immutability of blockchain provides a fertile environment for building high-quality, permanent, and increasing machine learning and deep learning datasets.


Furthermore, the combination of blockchain with machine learning and deep learning provides multiple benefits. It's a novel paradigm in which blockchain, machine learning, deep learning is combined to solve many real-time problems. This affects various fields such as the Internet of Things (IoT), smart city, healthcare, food and logistics, safety, automation in manufacturing, energy and utilities, civil governance, personalized medicine, and other industries, and thus bring benefits to many.


This special issue aim to highlight applications of these technologies in data security.


Blockchain, machine learning, deep learning, data security, artificial intelligence

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