Networking Data Integrity and Manipulation in Cyber-Physical and Communication Systems

This book offers a global perspective on the latest developments in data integrity and manipulation within cyber-physical and communication systems, with a focus on analytics and networking. It examines real-time data management and communication, emphasizing the temporal and spatial nature of data for effective sensing and actuation. It presents the latest developments in the technologies that lie at the intersection of data and networking to support cyber-physical and communication systems. These latest developments incorporate data analysis and manipulation relevant to the end-system smart devices and smart applications. They also include legacy Internet and Internet of Things networking and communication protocols, which are relevant because they tie together the end systems. The book addresses the technologies from the perspective of cyber-physical architectures. The book introduces real-world applications relevant to both researchers and technologists in academia and industry.

Presents latest data and networking technologies to support cyber-physical and communication systems Includes data analysis and manipulation relevant to the end-system smart devices and smart applications Addresses the technologies from the perspective of cyber-physical systems' solutions and architectures

Inhalt

Introduction to Networking Data Integrity and Manipulation in Cyber-Physical and Communication Systems.- Wireless Communication Protocols for the IoT - How to Choose the Best Option?.- Streaming Algorithms in Network Measurement.- Data Encryption for the TLS protocol against quantum adversaries.- Integrating the Self-Sovereign Identity in the TCP/IP Stack while Preserving Interoperability with Existing Identity Models.- Speech-Driven Medical Emergency Decision-Support Systems in Constrained Environments.- Networking Data Engineering: Bridging the Gap between Communication and Data Processing.- Integrative Cloud to Mist Computing: Architectures, Applications, and Innovations in Data Engineering.- Autonomic Cloud Computing: Research Perspective.- Physical Asset Virtualization Framework to support Cognitive Digital Twins.- Cloud Computing based Diabetes Prediction Framework with Risk Factor Analysis.- IoT and Digital Twin for Monitoring and Simulating Living Spaces Scenarios.- Building Trust in Spectrum Sharing: A Decentralized Architecture for Spectrum Databases.