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Full Description
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.
Contents
Chapter 1: Introduction to emerging security and privacy schemes for dense 6G wireless communication networks
Chapter 2: History of security and privacy in wireless communication systems: open research issues and future directions
Chapter 3: Artificial intelligence-enabled security systems for 6G wireless networks: algorithms, strategies, and applications
Chapter 4: The vision of 6G security and privacy
Chapter 5: Security threat landscape for 6G architecture
Chapter 6: Dynamic optical beam transmitter of secure visible light communication systems
Chapter 7: A new machine learning-based scheme for physical layer security
Chapter 8: Vehicular ad hoc networks employing intelligent reflective surfaces for physical layer security
Chapter 9: Physical layer security solutions and technologies
Chapter 10: Steganography-based secure communication via single carrier frequency division multiple access (SC-FDMA) transceiver
Chapter 11: A lightweight algorithm for the detection of fake incident reports in wireless communication systems
Chapter 12: A real-time intrusion detection system for service availability in cloud computing environments
Chapter 13: Addressing the security challenges of IoT-enabled networks using artificial intelligence, machine learning, and blockchain technology
Chapter 14: Alleviating 6G security and privacy issues using artificial intelligence
Chapter 15: Interference and phase noise in millimeter wave MIMO-NOMA and OFDM systems for beyond 5G networks
Chapter 16: A generative adversarial network-based approach for mitigating inference attacks in emerging wireless networks
Chapter 17: Adversarial resilience of self-normalizing convolutional neural networks for deep learning-based intrusion detection systems
Chapter 18: Legal frameworks for security schemes in wireless communication systems
Chapter 19: Design of a quantum true random number generator using quantum gates and benchmarking its performance on an IBM quantum-computer
Chapter 20: Security challenges and prospects of 6G network in cloud environments
