Xuemin (Sherman) Shen – författare

This SpringerBrief  covers the security and privacy challenges in fog computing, and proposes a  new secure and privacy-preserving mechanisms to resolve these challenges for securing fog-assisted IoT applications. Chapter 1 introduces the architecture of fog-assisted IoT applications and the security and privacy challenges in fog computing. Chapter 2 reviews several promising privacy-enhancing techniques and illustrates examples on how to leverage these techniques to enhance the privacy of users in fog computing. Specifically,  the authors divide the existing privacy-enhancing techniques into three categories: identity-hidden techniques, location privacy protection and data privacy enhancing techniques. The research is of great importance since security and privacy problems faced by fog computing impede the healthy development of its enabled IoT applications.

With the advanced privacy-enhancing techniques, the authors propose three secure andprivacy-preserving protocols for fog computing applications, including smart parking navigation, mobile crowdsensing and smart grid.  Chapter 3 introduces identity privacy leakage in smart parking navigation systems, and proposes a privacy-preserving smart parking navigation system to prevent identity privacy exposure and support efficient parking guidance retrieval through road-side units (fogs) with high retrieving probability and security guarantees. Chapter 4 presents the location privacy leakage, during task allocation in mobile crowdsensing, and propose a strong privacy-preserving task allocation scheme that enables location-based task allocation and reputation-based report selection without exposing knowledge about the location and reputation for participators in mobile crowdsensing. Chapter 5 introduces the data privacy leakage in smart grid, and proposes an efficient and privacy-preserving smart metering protocol to allow collectors (fogs) to achieve real-time measurement collection with privacy-enhanced data aggregation. Finally, conclusions and future research directions are given in Chapter 6.

 This brief validates the significant feature extension and efficiency improvement of IoT devices without sacrificing the security and privacy of users against dishonest fog nodes. It also provides valuable insights on the security and privacy protection for fog-enabled IoT applications. Researchers and professionals who carry out research on security and privacy in wireless communication will want to purchase this SpringerBrief.  Also, advanced level students,  whose main research area is mobile network security will also be interested in this SpringerBrief. 

This book covers the fundamental principles, new theories and methodologies, and potential applications of hybrid intelligent networks. Chapters focus on  hybrid neural networks and networked multi-agent networks, including their communication, control and optimization synthesis. This text also provides a succinct but useful guideline for designing neural network-based hybrid artificial intelligence for brain-inspired computation systems and applications in the Internet of Things.

Artificial Intelligence has developed into a deep research field targeting robots with more brain-inspired perception, learning, decision-making abilities, etc. This text devoted to a tutorial on hybrid intelligent networks that have been identified in nature and engineering, especially in the brain, modeled by hybrid dynamical systems and complex networks, and have shown potential application to brain-inspired intelligence. Included in this text are impulsive neural networks, neurodynamics, multiagent networks, hybrid dynamics analysis, collective dynamics, as well as hybrid communication, control and optimization methods.

Graduate students who are interested in artificial intelligence and hybrid intelligence, as well as professors and graduate students who are interested in neural networks and multiagent networks will find this textbook a valuable resource. AI engineers and consultants who are working in  wireless communications and networking will want to buy this book. Also, professional and academic institutions in universities and Mobile vehicle companies and engineers and managers who concern humans in the loop of IoT will also be interested in this book.

This book introduces the Internet access for vehicles as well as novel communication and computing paradigms based on the Internet of vehicles. 

To enable efficient and reliable Internet connection for mobile vehicle users, this book first introduces analytical modelling methods for the practical vehicle-to-roadside (V2R) Internet access procedure, and employ the interworking of V2R and vehicle-to-vehicle (V2V) to improve the network performance for a variety of automotive applications. 

In addition, the wireless link performance between a vehicle and an Internet access station is investigated, and a machine learning based algorithm is proposed to improve the link throughout by selecting an efficient modulation and coding scheme.

This book also investigates the distributed machine learning algorithms over the Internet access of vehicles. A novel broadcasting scheme is designed to intelligently adjust the training users that are involved in the iteration rounds for an asynchronous federated learning scheme, which is shown to greatly improve the training efficiency. This book conducts the fully asynchronous machine learning evaluations among vehicle users that can utilize the opportunistic V2R communication to train machine learning models. 

Researchers and advanced-level students who focus on vehicular networks, industrial entities for internet of vehicles providers, government agencies target on transportation system and road management will find this book useful as reference. Network device manufacturers and network operators will also want to purchase this book. 

This book provides a comprehensive investigation on new technologies for future vehicular networks. The authors propose different schemes to efficiently manage the multi-dimensional resources for supporting diversified applications. The authors answer the questions of why connected and automated vehicle technology should be considered; how the multi-access edge computing (MEC) and unmanned aerial vehicle (UAV) technologies can be helpful to vehicular networks; how to efficiently manage the multi-dimensional resources to support different vehicular applications with guaranteed quality-of-service (QoS) requirements; and how to adopt optimization and AI technologies to achieve resource management in vehicular networks. The book is pertinent to researchers, professionals, academics and students in vehicular technologies.

This book proposes secure schemes to address security challenges in secure automatic dependent surveillance-broadcast systems (ADS-B) from five different angles. First, the authors examine encryption schemes applied to the ADS-B environment for protecting messages confidentiality. Second, they propose an ADS-B broadcast authentication scheme with batch verification by employing an identity-based signature. Third, they present ADS-B broadcast authentication scheme based on a digital signature with message recovery, which provides a feature that the message is recoverable from the signature. Fourth, they propose a new cryptographic solution to ADS-B security. Finally, they propose an accurate and efficient cognitive aircraft location verification scheme preserving aircraft location privacy by utilizing a grid-based k-nearest neighbor algorithm. In summary, the authors show how ADS-B data links can greatly enhance flight safety by these proposed schemes without sacrificing data security.

Proposes several secure schemes to address security challenges in secure automatic dependent surveillance-broadcast systems (ADS-B);

Provides extensive experiments and evaluates the proposed schemes using real-world data;

Shows how ADS-B data links can greatly enhance safety without sacrificing data security

This book investigates intelligent network resource management for IoV, with the objective of maximizing the communication and computing performance of vehicle users. Focusing on two representative use cases in IoV, i.e., safety message broadcast and autonomous driving, the authors propose link-layer protocol design and application-layer computing task scheduling to achieve the objective given the unique characteristics and requirements of IoV. In particular, this book illustrates the challenges of resource management for IoV due to network dynamics, such as time-varying traffic intensity and vehicle mobility, and presents intelligent resource management solutions to adapt to the network dynamics. The Internet of  Vehicles (IoV) enables vehicle-to-everything connectivity and supports a variety of applications for vehicles on the road.

Intelligent resource management is critical for satisfying demanding communication and computing requirements on IoV, while the highly dynamic network environments pose challenges to the design of resource management schemes. This book provides insights into the significance of adaptive resource management in improving the performance of IoV. The customized communication protocol and computing scheduling scheme are designed accordingly by taking the network dynamics information as an integral design factor. Moreover, the decentralized designs of the proposed solutions guarantee low signaling overhead and high scalability.

A comprehensive literature review summarizing recent resource management schemes in IoV, followed by the customized design of communication and computing solutions for the two IoV use cases is included which can serve as a useful reference for professionals from both academia and industry in the area of IoV and resource management.  Researchers working within this field and computer science and electrical engineering students will find this book useful as well.

This book presents the security and privacy challenges of the smart home following the logic of “terminal device – voice interface – application platform”. For each component, the authors provide answers to the three questions: 1) In the terminal device layer, how to conduct cross-layer privacy breach analysis and provide effective countermeasures; 2) In the voice interface layer, how to design effective and lightweight schemes to defend against voice spoofing; 3) In the application layer, how to design an effective anomaly detection system without breaching the application platform. The authors conduct a thorough analysis of the security threats and challenges in each component of the smart home, review the existing state-of-the-art solutions proposed by other researchers, and elaborate on proposed countermeasures. This book aims to provide both security threats analysis and state-of-the-art countermeasures for the smart home network.