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COMPUTATIONAL INTELLIGENCE AND BLOCKCHAIN IN COMPLEX SYSTEMS : system security and interdisciplinary applications /

Computational Intelligence and Blockchain in Complex Systems provides readers with a guide to understanding the dynamics of AI, Machine Learning, and Computational Intelligence in Blockchain, and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fi...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Al-Turjman, Fadi (Editor)
Format: eBook
Language:English
Published: Cambridge, MA : MORGAN KAUFMANN, 2024.
Series:Advanced studies in complex systems.
Subjects:
Blockchains (Databases)
Computer security.
Chaînes de blocs.
Sécurité informatique.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front Cover
  • Computational Intelligence and Blockchain in Complex Systems
  • Copyright Page
  • Dedication
  • Contents
  • List of contributors
  • 1 An overview of future cyber security applications using AI and blockchain technology
  • 1.1 Introduction
  • 1.2 Previous work extent
  • 1.3 Using blockchain technologies in cyber security
  • 1.4 Blockchain applications in cybersecurity
  • 1.5 The application of artificial intelligence technologies in cyber security
  • 1.6 The benefits of artificial intelligence in cybersecurity
  • 1.7 Here are a few advantages and applications of artificial intelligence in cybersecurity
  • 1.8 Conclusion
  • References
  • 2 A survey of issues, possibilities, and solutions for a blockchain and AI-powered Internet of things
  • 2.1 Introduction
  • 2.2 The volume of prior work
  • 2.3 Internet of things driven by 6G
  • 2.4 What is blockchain, anyway?
  • 2.5 Blockchain with artificial intelligence: challenges, opportunities, and solutions for the 6G internet of things
  • 2.6 Discussion
  • 2.7 Conclusion
  • References
  • 3 A simple online payment system using blockchain technology
  • 3.1 Introduction
  • 3.1.1 Objectives
  • 3.2 Research and design
  • 3.2.1 Blockchain technology and its application on online payment systems
  • 3.2.2 Designing the architecture of the online payment system
  • 3.2.3 Integration of the Metamask API into the online payment system using Python
  • 3.2.4 User interface design of the proposed system
  • 3.3 Conclusions
  • References
  • 4 Efficient spam email classification logistic regression model trained by modified social network search algorithm
  • 4.1 Introduction
  • 4.2 Background and literature review
  • 4.2.1 Logistic regression
  • 4.2.2 Metaheuristic optimization
  • 4.3 Proposed hybrid metaheuristics
  • 4.3.1 Introduced social network search algorithm
  • 4.3.2 Novel initialization scheme.
  • 4.3.3 Strategy for preserving population heterogeneity
  • 4.3.4 Inner functioning and complexity of the proposed algorithm
  • 4.4 Experiments and comparative analysis
  • 4.4.1 Dataset and preprocessing
  • 4.4.2 Experimental setup
  • 4.4.3 Obtained simulation outcomes and comparative analysis
  • 4.5 Conclusion
  • References
  • 5 Reviewing artificial intelligence and blockchain innovations: transformative applications in the energy sector
  • 5.1 Introduction
  • 5.2 Literature review
  • 5.2.1 Background of blockchain technology
  • 5.2.2 Distributed energy resources, a new paradigm
  • 5.2.3 Consensus algorithms
  • 5.3 Applications of artificial intelligence and blockchain in the energy industry
  • 5.3.1 Artificial intelligence in solar energy: yield performance predictions
  • 5.3.2 Using artificial intelligence to improve energy performance
  • 5.3.3 Artificial intelligence in grid management
  • 5.3.4 Solar coin use on blockchain for renewables
  • 5.3.5 Trading in energy (blockchain using peer-to-peer and artificial intelligence technologies)
  • 5.3.6 Intelligent grids
  • 5.3.7 Grid security
  • 5.3.8 Grid administration and efficiency
  • 5.3.9 Increased productivity
  • 5.3.10 Predictive analytics
  • 5.3.11 Storage of energy
  • 5.3.12 Trading in energy
  • 5.3.13 Power theft and energy fraud detection
  • 5.3.14 Microgrids
  • 5.3.15 Customer engagement
  • 5.4 Use cases
  • 5.4.1 Powerledger
  • 5.4.2 Energy web foundation
  • 5.4.3 Verv
  • 5.5 Discussions
  • 5.5.1 Comparison between Solana and the Ethereum network
  • 5.5.1.1 Tesla power and Powerlegder
  • 5.6 Conclusion
  • References
  • 6 Using artificial intelligence in education applications
  • 6.1 Introduction
  • 6.2 Extent of past work
  • 6.3 Materials and methods
  • 6.4 Result and discussion
  • 6.5 Conclusion
  • References.
  • 7 Performance measurements of 12 different machine learning algorithms that make personalized psoriasis treatment recommend...
  • 7.1 Introduction and literature review
  • 7.2 Materials and methods
  • 7.2.1 Logistic regression
  • 7.2.2 Gaussian naive Bayes
  • 7.2.3 K-Nearest neighbors
  • 7.2.4 Support vector classification
  • 7.2.5 Radial basis function
  • 7.2.6 Artificial neural network
  • 7.2.7 Cart algorithm
  • 7.2.8 Random forest
  • 7.2.9 Gradient boosting machines
  • 7.2.10 XGBoost
  • 7.2.11 LightGBM
  • 7.2.12 CatBoost
  • 7.3 Experimental results
  • 7.4 Conclusion and future work
  • References
  • 8 Healthcare cybersecurity challenges: a look at current and future trends
  • 8.1 Introduction
  • 8.2 The amount of prior works
  • 8.3 Difficulties
  • 8.3.1 Security assurance for remote work
  • 8.3.2 Endpoint device administration
  • 8.3.3 The role of humans in cybersecurity
  • 8.3.4 A disregard for security
  • 8.3.5 Ineffective risk assessment communication at the board level
  • 8.3.6 Poor business continuity strategies
  • 8.3.7 Ineffective incident response coordination
  • 8.3.8 A tight budget and the requirement to provide healthcare services uninterrupted
  • 8.3.9 Dangerous medical cyber-physical systems
  • 8.4 A review of current and future trends in cybersecurity challenges in healthcare
  • 8.5 Discussion
  • 8.5.1 Cyber-physical medical systems
  • 8.5.2 Data privacy, confidentiality, and consent
  • 8.5.3 Cloud computing
  • 8.5.4 Malware
  • 8.5.5 Security of health application (or "app")
  • 8.5.6 Insider danger
  • 8.6 Cybersecurity tools, defenses, and mitigation techniques
  • 8.6.1 Cryptographic systems or other technological advances
  • 8.6.2 Governance and risk assessment
  • 8.6.3 Laws or other regulations
  • 8.6.4 A comprehensive strategy for proactive cybersecurity culture
  • 8.6.5 Instruction and simulated settings.
  • 8.6.6 Cyber maturity and capability
  • 8.6.7 Cyber-hygiene procedures
  • 8.7 Conclusion
  • References
  • 9 EU artificial intelligence regulation
  • 9.1 Introduction
  • 9.2 Background of the regulation
  • 9.2.1 Digital Decade targets and objectives
  • 9.2.2 2030 Targets of European Union
  • 9.2.3 Multicountry projects
  • 9.2.4 Road map
  • 9.3 Scope of the regulation
  • 9.3.1 What is the Artificial Intelligence Act?
  • 9.3.2 Risk assessment
  • 9.3.3 Innovation and implementation
  • 9.3.4 The harm requirement
  • 9.3.5 Current European Union legislation comparison
  • 9.4 Conclusion
  • References
  • 10 The issue of personality rıghts and artıfıcıal intellıgence
  • 10.1 Introduction
  • 10.2 Person and personality
  • 10.2.1 Capacity to have right and capacity to act
  • 10.3 Artificial intelligence and personality
  • 10.3.1 Ideas that artificial intelligence can not have a legal personality
  • 10.3.2 Ideas that artificial intelligence can have a legal personality
  • 10.4 Conclusion
  • References
  • 11 Will artificial intelligence sit on the judge's bench?
  • 11.1 Introduction
  • 11.1.1 Is jurisdiction a means of solving problems?
  • 11.2 Can artificial intelligence realize law?
  • 11.3 Can artificial intelligence interpret or create law?
  • 11.4 Conclusion
  • References
  • 12 The effectiveness of virtual reality-based technology on foreign language vocabulary teaching to children with attention...
  • 12.1 Introduction
  • 12.1.1 The impact that having attention deficit hyperactivity disorder has on a student's ability to succeed academically
  • 12.1.2 The use of interventions for students diagnosed with attention deficit hyperactivity disorder
  • 12.1.3 Interventions performed in a clinic
  • 12.1.4 Technology in education
  • 12.1.5 The environments for virtual reality education
  • 12.2 Method
  • 12.2.1 Participants
  • 12.2.2 Materials.
  • 12.2.2.1 Cinema video player plugin
  • 12.2.2.2 Virtual reality-based teaching material
  • 12.2.2.2.1 Equipment used
  • 12.2.2.2.2 Preparing the learning environment
  • 12.2.2.2.3 Adaptation to virtual reality
  • 12.2.3 Intervention procedure
  • 12.2.4 Limitations
  • 12.2.5 Validity
  • 12.2.5.1 Experimental control/internal validity
  • 12.2.5.2 Inter-rater agreement
  • 12.2.5.3 Fidelity
  • 12.2.5.4 Social validity
  • 12.3 Results
  • 12.4 Conclusion
  • References
  • 13 BERT-IDS: an intrusion detection system based on bidirectional encoder representations from transformers
  • 13.1 Introduction
  • 13.2 Review of related works
  • 13.3 Dataset
  • 13.4 Method
  • 13.5 Results and analysis
  • 13.6 Conclusion
  • References
  • 14 Internet of Things and the electrocardiogram using artificial intelligence-a survey
  • 14.1 Introduction
  • 14.2 Literature study on electrocardiogram
  • 14.2.1 What is electrocardiogram
  • 14.2.2 Diseases the electrocardiogram detects
  • 14.3 Electrocardiogram signal
  • 14.4 Review of technique used in electrocardiogram
  • 14.4.1 Genetic algorithm-back propagation neural network
  • 14.4.2 Back propagation neural network
  • 14.4.3 Artificial neural network
  • 14.5 Conclusion
  • References
  • 15 Evaluation of artificial intelligence in education and its applications according to the opinions of school administrators
  • 15.1 Introduction
  • 15.2 Method
  • 15.2.1 Model of the research
  • 15.2.2 Data collection tool
  • 15.2.3 Working group
  • 15.2.4 Data collection
  • 15.2.5 Analysis of data
  • 15.3 Findings and comments
  • 15.4 Conclusion and recommendations
  • References
  • 16 Evaluation of tourism developments with artificial intelligence according to the opinions of tourism hotel managers
  • 16.1 Introduction
  • 16.2 Artificial intelligence in tourism
  • 16.3 Use of artificial intelligence in hotels
  • 16.4 Methodology.