Cyber Security In Parallel And Distributed Computing
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Cyber Security in Parallel and Distributed Computing
The book contains several new concepts, techniques, applications and case studies for cyber securities in parallel and distributed computing The main objective of this book is to explore the concept of cybersecurity in parallel and distributed computing along with recent research developments in the field. Also included are various real-time/offline applications and case studies in the fields of engineering and computer science and the modern tools and technologies used. Information concerning various topics relating to cybersecurity technologies is organized within the sixteen chapters of this book. Some of the important topics covered include: Research and solutions for the problem of hidden image detection Security aspects of data mining and possible solution techniques A comparative analysis of various methods used in e-commerce security and how to perform secure payment transactions in an efficient manner Blockchain technology and how it is crucial to the security industry Security for the Internet of Things Security issues and challenges in distributed computing security such as heterogeneous computing, cloud computing, fog computing, etc. Demonstrates the administration task issue in unified cloud situations as a multi-target enhancement issue in light of security Explores the concepts of cybercrime and cybersecurity and presents the statistical impact it is having on organizations Security policies and mechanisms, various categories of attacks (e.g., denial-of-service), global security architecture, along with distribution of security mechanisms Security issues in the healthcare sector with existing solutions and emerging threats.
Distributed and Cloud Computing
Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. - Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing - Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more - Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery - Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online
Artificial Intelligence for Cyber Security and Industry 4.0
Artificial Intelligence for Cyber Security and Industry 4.0 offers a comprehensive exploration of the intersection of artificial intelligence (AI) and cyber security, providing readers with a thorough understanding of both the advantages and risks posed by AI technologies in modern industries. Covering a wide array of topics, from data anonymization and intrusion detection to AI's role in cloud security, border surveillance, and healthcare, this book addresses current challenges and proposes innovative solutions. It also highlights ethical concerns related to AI's use in weapon autonomy and border migration. This book is ideal for researchers, industry professionals, policy makers, and students looking to deepen their knowledge of AI's impact on cyber security and its applications in the evolving landscape of Industry 4.0. Through practical insights and forward-thinking discussions, readers will gain a well-rounded perspective on how AI can be leveraged for security while being mindful of emerging risks. Key Features: Explores the dual role of AI in strengthening and threatening cyber security in the context of Industry 4.0 Provides an in-depth analysis of AI-driven cyber security techniques, including machine learning-based intrusion detection and data anonymization Investigates the malicious use of AI, addressing both expanded existing threats and the emergence of novel vulnerabilities Discusses advanced software design for privacy preservation in big data environments Covers the use of AI in specific security domains, such as border surveillance, healthcare, and the Internet of Things Highlights AI applications in cloud security, data integrity, and privacy protection Introduces Quantum Machine Learning algorithms and their relevance to cyber security Explores the ethical concerns surrounding AI technologies, particularly in the context of weapon autonomy and border migration Includes real-world scenarios and methodologies, bridging the gap between academic research and industry practice Offers forward-looking insights into the role of AI in future cyber security challenges and solutions