This SpringerBrief focuses on spectrum trading designs in multi-hop cognitive radio networks. It starts with the motivation for spectrum trading and the review of existing spectrum trading designs. Then, it presents a novel CRN architecture for spectrum trading considering spectrum trading's economic features and wireless nature. Under this network architecture, it extends current single-hop per-user based spectrum trading design into a multi-hop transmission opportunity based one, and further into a session based one, while having economic properties guaranteed. This SpringerBrief not only provides a good review of current spectrum trading designs, it also touches on the cutting-edge interdisciplinary spectrum trading research on disparate fields of modeling, network architecture design, optimization theories, statistics, and economic theories. Advanced-level students studying computer science, electrical and computer engineering and economics, wireless network planners, and wireless spectrum engineers will find this book a useful tool.

This SpringerBrief mainly focuses on effective big data analytics for CPS, and addresses the privacy issues that arise on various CPS applications. The authors develop a series of privacy preserving data analytic and processing methodologies through data driven optimization based on applied cryptographic techniques and differential privacy in this brief. This brief also focuses on effectively integrating the data analysis and data privacy preservation techniques to provide the most desirable solutions for the state-of-the-art CPS with various application-specific requirements. Cyber-physical systems (CPS) are the "next generation of engineered systems," that integrate computation and networking capabilities to monitor and control entities in the physical world. Multiple domains of CPS typically collect huge amounts of data and rely on it for decision making, where the data may include individual or sensitive information, for e.g., smart metering, intelligent transportation, healthcare, sensor/data aggregation, crowd sensing etc. This brief assists users working in these areas and contributes to the literature by addressing data privacy concerns during collection, computation or big data analysis in these large scale systems. Data breaches result in undesirable loss of privacy for the participants and for the entire system, therefore identifying the vulnerabilities and developing tools to mitigate such concerns is crucial to build high confidence CPS. This Springerbrief targets professors, professionals and research scientists working in Wireless Communications, Networking, Cyber-Physical Systems and Data Science. Undergraduate and graduate-level students interested in Privacy Preservation of state-of-the-art Wireless Networks and Cyber-Physical Systems will use this Springerbrief as a study guide.