Fifth generation (5G) wireless networks are now commercialized, and the research focus has shifted towards sixth generation (6G) wireless systems. The integration of sensor nodes and massive machine type communication (MTC) devices (MDs) in ubiquitous 5G networks has facilitated the design of critical enabling technologies to support billions of data-hungry applications. By leveraging sensor nodes in wireless sensor networks (WSNs), sensitive user information can be harvested and transmitted to receivers via WSN-assisted channels, which are often not well secured. Consequently, sensitive user information can be intercepted and used unlawfully. The security and confidentiality measures used for data transmission over existing 5G WSN-assisted channels are limited. 6G systems are envisaged to face fiercer security challenges. In 6G wireless networks, a new set of sensing and precise localization techniques are predicted. Thus, the need to secure user information against adversarial attacks needs to be implemented at the design stage.The book proposes viable solutions to revamp traditional security architecture by addressing critical security challenges in commercialized 5G and envisioned 6G wireless communication systems. Expert contributors bring new insights into real-world scenarios for the deployment, applications and management of robust, secure, and efficient security schemes for massive devices in 6G wireless networks. Finally, the book discusses critical security and privacy issues affecting the wireless ecosystem and provides practical AI-based solutions.Security and Privacy Schemes for Dense 6G Wireless Communication Networks is an essential reference for industry and academic researchers; scientists, engineers, lecturers and advanced students in the fields of cybersecurity wireless communication and networking, network security, computing, data science, AI/ML/DL, and sensing, as well as cybersecurity professionals and 6G standardization experts.

The expansion of telehealth services is enabling healthcare professionals to consult, diagnose, advise or perform tasks remotely, enabling them to treat more patients in their own homes or consult on cases on the other side of the world. The security of sensitive user information is critical to effective and efficient delivery of healthcare services. Artificial intelligence (AI) and blockchain technology are identified as key drivers of emerging telehealth systems, enabling efficient delivery of telehealth services to billions of patients globally. Specifically, AI facilitates the processing and analysis of complex telehealth data, and blockchain technology offers decentralised, transparent, traceable, reliable, trustful, and provable security to telehealth systems.This edited book reviews security and privacy issues in traditional telehealth systems and focuses on the technical considerations, potential opportunities and critical challenges currently inhibiting the adoption of AI and blockchain in telehealth systems. The book presents case studies which highlight critical lessons and considers the prospects and societal benefits of AI and blockchain, while providing suitable recommendations for designing future AI and blockchain-based telehealth systems.Artificial Intelligence and Blockchain Technology in Modern Telehealth Systems is suited to researchers and computer engineers working in healthcare delivery, telemedicine, cybersecurity, data science, AI/ML and those in related fields.

Fifth generation (5G) wireless networks are now commercialized, and the research focus has shifted towards sixth generation (6G) wireless systems. The integration of sensor nodes and massive machine type communication (MTC) devices (MDs) in ubiquitous 5G networks has facilitated the design of critical enabling technologies to support billions of data-hungry applications. By leveraging sensor nodes in wireless sensor networks (WSNs), sensitive user information can be harvested and transmitted to receivers via WSN-assisted channels, which are often not well secured. Consequently, sensitive user information can be intercepted and used unlawfully. The security and confidentiality measures used for data transmission over existing 5G WSN-assisted channels are limited. 6G systems are envisaged to face fiercer security challenges. In 6G wireless networks, a new set of sensing and precise localization techniques are predicted. Thus, the need to secure user information against adversarial attacks needs to be implemented at the design stage.The book proposes viable solutions to revamp traditional security architecture by addressing critical security challenges in commercialized 5G and envisioned 6G wireless communication systems. Expert contributors bring new insights into real-world scenarios for the deployment, applications and management of robust, secure, and efficient security schemes for massive devices in 6G wireless networks. Finally, the book discusses critical security and privacy issues affecting the wireless ecosystem and provides practical AI-based solutions.Security and Privacy Schemes for Dense 6G Wireless Communication Networks is an essential reference for industry and academic researchers; scientists, engineers, lecturers and advanced students in the fields of cybersecurity wireless communication and networking, network security, computing, data science, AI/ML/DL, and sensing, as well as cybersecurity professionals and 6G standardization experts.

The expansion of telehealth services is enabling healthcare professionals to consult, diagnose, advise or perform tasks remotely, enabling them to treat more patients in their own homes or consult on cases on the other side of the world. The security of sensitive user information is critical to effective and efficient delivery of healthcare services. Artificial intelligence (AI) and blockchain technology are identified as key drivers of emerging telehealth systems, enabling efficient delivery of telehealth services to billions of patients globally. Specifically, AI facilitates the processing and analysis of complex telehealth data, and blockchain technology offers decentralised, transparent, traceable, reliable, trustful, and provable security to telehealth systems.This edited book reviews security and privacy issues in traditional telehealth systems and focuses on the technical considerations, potential opportunities and critical challenges currently inhibiting the adoption of AI and blockchain in telehealth systems. The book presents case studies which highlight critical lessons and considers the prospects and societal benefits of AI and blockchain, while providing suitable recommendations for designing future AI and blockchain-based telehealth systems.Artificial Intelligence and Blockchain Technology in Modern Telehealth Systems is suited to researchers and computer engineers working in healthcare delivery, telemedicine, cybersecurity, data science, AI/ML and those in related fields.