Abstract

Cybercrime is a vast and flourishing underground industry that poses a real and disruptive threat to every profession, industry, and company in the world. Blockchain has emerged as a promising technology for securing critical data and operations. However, blockchain networks are not immune to cybersecurity vulnerabilities. This chapter sheds light on the cybersecurity vulnerabilities of both public and private blockchain networks. It also provides a mathematical model based on graph theory that can be used to assess cyber vulnerabilities for a given blockchain design. The chapter concludes by discussing the intersection between machine learning, artificial intelligence, and blockchain, specifically, the use of blockchain trust fabric to enable federated machine learning.

Original languageEnglish (US)
Title of host publicationBlockchains
Subtitle of host publicationEmpowering Technologies and Industrial Applications
PublisherWiley
Pages215-251
Number of pages37
ISBN (Electronic)9781119781042
ISBN (Print)9781119781011
DOIs
StatePublished - Jan 1 2023

Keywords

  • artificial intelligence
  • blockchain
  • cybercrime
  • cybersecurity
  • federated machine learning
  • graph theory
  • machine learning

ASJC Scopus subject areas

  • General Engineering
  • General Computer Science

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