Blockchains for Network Security - (Computing and Networks) by Haojun Huang & Lizhe Wang & Yulei Wu & Kim-Kwang Raymond Choo (Hardcover)
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<p/><br></br><p><b> About the Book </b></p></br></br><p>Presenting a comprehensive view of blockchain technologies for network security from principles to core technologies and applications, this book offers unprecedented insights into recent advances and developments in these areas, and how they can make blockchain technologies associated with networks more secure and fit-for-purpose.</p><p/><br></br><p><b> Book Synopsis </b></p></br></br><p>Blockchain technology is a powerful, cost-effective method for network security. Essentially, it is a decentralized ledger for storing all committed transactions in trustless environments by integrating several core technologies such as cryptographic hash, digital signature and distributed consensus mechanisms.</p> <p>Over the past few years, blockchain technology has been used in a variety of network interaction systems such as smart contracts, public services, Internet of Things (IoT), social networks, reputation systems and security and financial services. With its widespread adoption, there has been increased focus on utilizing blockchain technologies to address network security concerns and vulnerabilities as well as understanding real-world security implications.</p> <p>The book begins with an introduction to blockchains, covering key principles and applications. Further chapters cover blockchain system architecture, applications and research issues; blockchain consensuses and incentives; blockchain applications, projects and implementations; blockchain for internet of things; blockchain in 5G and 6G networks; edgechain to provide security in organization based multi agent systems; blockchain driven privacy-preserving machine learning; performance evaluation of differential privacy mechanisms in blockchain based smart metering; scaling-out blockchains with sharding; blockchain for GIS; and finally blockchain applications in remote sensing big data management and production.</p>
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