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.

• 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