Security and Privacy Schemes for Dense 6G Wireless Communication Networks
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Agbotiname Lucky Imoize is a lecturer in the Department of Electrical and Electronics Engineering at the University of Lagos, Nigeria. His research interests cover the fields of 6G wireless communication, wireless security systems, and artificial intelligence. He is a registered engineer with the Council for the Regulation of Engineering in Nigeria (COREN), the vice chair of the IEEE Communication Society, Nigeria chapter, and a senior member of the IEEE. Chandrashekhar Meshram is assistant professor in the Department of Post Graduate Studies and Research in Mathematics, Jaywanti Haksar Government Post Graduate College, Raja Shankar Shah University, India. His research interests include cryptography and its applications, neural networks, the IoT, wireless sensor networks (WSNs), medical information systems, ad hoc networks, number theory, fuzzy theory, time series analysis, climate change, mathematical modeling, and chaos theory. He has published over 110 scientific articles in international journals and conferences. Dinh-Thuan Do is an assistant professor of Computer and Electrical Engineering in the School of Engineering at the University of Mount Union, USA. His research interests include signal processing in wireless communications networks, non-orthogonal multiple access, full-duplex transmission, and reconfigurable intelligent surfaces (RIS). He was a recipient of the Golden Globe Award from the Vietnamese Ministry of Science and Technology in 2015 (Top ten excellent scientists nationwide). He is a senior member of the IEEE. Seifedine Kadry is a professor at Lebanese American University, Lebanon, and Noroff University College, Norway. His research focuses on data science education using technology, system prognostics, stochastic systems, and applied mathematics. He is also an ABET program evaluator for computing and for Engineering Tech. He is a fellow of the IET, IETE, and IACSIT, and a distinguished speaker of the IEEE Computer Society. Lakshmanan Muthukaruppan is a professor, head of the Department of Electronics and Communication Engineering and dean of research at Galgotias College of Engineering and Technology, Uttar Pradesh, India. His research interests include wireless communication and networks, security algorithms, digital communication, information coding theory, signal and image processing, deep learning, and machine learning. He has published over 70 papers in journals and conferences and has four patents issued in India and two patents granted in Australia.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 book proposes solutions to revamp traditional security architecture by addressing critical security challenges in commercialized 5G and envisioned 6G wireless communication systems. New insights into real-world scenarios for the deployment, applications and management of robust, secure, and efficient security schemes are discussed.
- 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