Future Trends In Blockchain Scalability Interoparability And Beyond Machine Learning
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FUTURE TRENDS IN BLOCKCHAIN SCALABILITY, INTEROPARABILITY, AND BEYOND MACHINE LEARNING
Author: Manoj Ram Tammina
language: en
Publisher: Xoffencerpublication
Release Date: 2023-10-30
A blockchain is a distributed public ledger that records transactions in a series of linked blocks that can be accessed by anyone. Before being added to the chain, the data (block) is time-stamped and verified. Each block builds upon the data in the one before it. The data is very difficult to forge due to the mathematical complexity of the storage system. The legacy of cryptocurrencies has helped turn the cryptographic term "blockchain" into a trendy catchphrase. A lot of people think blockchain is the same thing as cryptocurrencies. The opposite is true. Blockchain is the underlying technology behind cryptocurrencies, but its uses extend well beyond that. Blockchains may be considered for use in situations requiring the validation, auditing, or exchange of data. Here, we survey the literature on integrating blockchain with machine learning, and show that the two may work together successfully and efficiently. Machine learning is an umbrella word that includes a wide range of techniques, such as traditional ML, DL, and RL. As a distributed and append-only ledger system, the blockchain is a natural instrument for sharing and processing large data from multiple sources thanks to the inclusion of smart contracts, which is a crucial component of the infrastructure necessary for big data analysis. When it comes to training and testing machine learning models, blockchain can keep data secure and promote data exchange. In addition, it paves the way for the creation of timely prediction models using several data sources by leveraging distributed computing resources (like IoT). This is crucial for deep learning processes, which need a lot of processing time. However, distributed systems are more difficult to monitor and regulate than centralized ones, and blockchain systems will create a massive quantity of data from a variety of sources. The best blockchain mechanism designs need accurate data analysis and predictions of system behaviors. Data verification, as well as the detection of harmful assaults and dishonest transactions on the blockchain, may be aided by machine learning. There is a lot to gain from studying how to merge the two technologies from different perspectives.
Artificial Intelligence in Healthcare
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Proceedings of the 19th International Conference on Cyber Warfare and Security
Author: UKDr. Stephanie J. Blackmonand Dr. Saltuk Karahan
language: en
Publisher: Academic Conferences and publishing limited
Release Date: 2025-04-20
The International Conference on Cyber Warfare and Security (ICCWS) is a prominent academic conference that has been held annually for 20 years, bringing together researchers, practitioners, and scholars from around the globe to discuss and advance the field of cyber warfare and security. The conference proceedings are published each year, contributing to the body of knowledge in this rapidly evolving domain. The Proceedings of the 19th International Conference on Cyber Warfare and Security, 2024 includes Academic research papers, PhD research papers, Master’s Research papers and work-in-progress papers which have been presented and discussed at the conference. The proceedings are of an academic level appropriate to a professional research audience including graduates, post-graduates, doctoral and and post-doctoral researchers. All papers have been double-blind peer reviewed by members of the Review Committee.