Cybersecurity Vigilance And Security Engineering Of Internet Of Everything
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Cybersecurity Vigilance and Security Engineering of Internet of Everything
Author: Kashif Naseer Qureshi
language: en
Publisher: Springer Nature
Release Date: 2023-11-30
This book first discusses cyber security fundamentals then delves into security threats and vulnerabilities, security vigilance, and security engineering for Internet of Everything (IoE) networks. After an introduction, the first section covers the security threats and vulnerabilities or techniques to expose the networks to security attacks such as repudiation, tampering, spoofing, and elevation of privilege. The second section of the book covers vigilance or prevention techniques like intrusion detection systems, trust evaluation models, crypto, and hashing privacy solutions for IoE networks. This section also covers the security engineering for embedded and cyber-physical systems in IoE networks such as blockchain, artificial intelligence, and machine learning-based solutions to secure the networks. This book provides a clear overview in all relevant areas so readers gain a better understanding of IoE networks in terms of security threats, prevention, and other security mechanisms.
Convergence of Blockchain, Internet of Everything, and Federated Learning for Security
The convergence of blockchain, the Internet of Everything (IoE), and federated learning paves the way for enhanced security in digital ecosystems. Blockchain offers decentralized, tamper-proof solutions that ensure data integrity, while the IoE connects smart devices, generating large amounts of data that require robust protection. Federated learning allows models to be trained locally on edge devices without transferring sensitive data to centralized servers, minimizing exposure to cyber threats. These technologies strengthen privacy and data security while enabling more efficient, scalable, and resilient systems. Further research into the potential of these technologies may redefine how security is managed, ensuring a safer environment for individuals and organizations. Convergence of Blockchain, Internet of Everything, and Federated Learning for Security explores the convergence of blockchain, IoEs, federated learning, and cybersecurity, highlighting their relevance in the modern digital landscape. It examines the importance of these technologies in addressing security challenges and enhancing data privacy in interconnected systems. This book covers topics such as cryptography, machine learning, and smart grids, and is a useful resource for business owners, computer engineers, data scientists, academicians, and researchers.
Next Generation AI Language Models in Research
In this comprehensive and cutting-edge volume, Qureshi and Jeon bring together experts from around the world to explore the potential of artificial intelligence models in research and discuss the potential benefits and the concerns and challenges that the rapid development of this field has raised. The international chapter contributor group provides a wealth of technical information on different aspects of AI, including key aspects of AI, deep learning and machine learning models for AI, natural language processing and computer vision, reinforcement learning, ethics and responsibilities, security, practical implementation, and future directions. The contents are balanced in terms of theory, methodologies, and technical aspects, and contributors provide case studies to clearly illustrate the concepts and technical discussions throughout. Readers will gain valuable insights into how AI can revolutionize their work in fields including data analytics and pattern identification, healthcare research, social science research, and more, and improve their technical skills, problem-solving abilities, and evidence-based decision-making. Additionally, they will be cognizant of the limitations and challenges, the ethical implications, and security concerns related to language models, which will enable them to make more informed choices regarding their implementation. This book is an invaluable resource for undergraduate and graduate students who want to understand AI models, recent trends in the area, and technical and ethical aspects of AI. Companies involved in AI development or implementing AI in various fields will also benefit from the book’s discussions on both the technical and ethical aspects of this rapidly growing field.