The growth of the Internet of Things (IoT) technology has indeed led to an increase in cybersecurity issues. While the Internet of Things enhances accessibility, integrity, availability, scalability, confidentiality, and interoperability among devices, it also faces vulnerabilities due to its diverse attack sources and lack of standardization in security protocols. This makes Internet of Things systems particularly susceptible to cyberattacks. It is essential to ensure proper security measures are in place to protect Internet of Things devices and networks, given their critical role in modern communications and the evolving threat landscape. Always remember to verify important security information from trusted sources.
Recent Advances in Internet of Things Security discusses the critical importance of robust security frameworks to protect Internet of Things ecosystems against various cyber threats. It highlights the security risks associated with Internet of Things devices and applications and presents a variety of potential solutions. It is essential to remain aware of these challenges to effectively safeguard Internet of Things systems. This book delves into the complexities of IoT security, exploring a range of vulnerabilities across different layers of the IoT architecture.
The book provides a comprehensive overview of Internet of Things security, emphasizing the significance of securing Internet of Things products and applications. It serves as a foundational resource for young researchers, academics, and industry professionals keen on advanced security solutions within the Internet of Things landscape, reflecting the current state of research and ongoing challenges in this field.
Table of Contents:
Chapter 1 Strengthening IIoT security: Integrating intrusion detection systems with machine learning Chapter 2 Scalable IoT anomaly detection: Federated and split learning Chapter 3 Machine learning-based detection in wireless sensor networks Chapter 4 A secure approach for next-generation IoT networks: A comparative analysis Chapter 5 Efficient ECC-based RFID authentication for enhanced IoT security Chapter 6 An AI-based embedded system for access control and absence management Chapter 7 A new perspective on E-health perforated blockchain: An intelligent healthcare revolution using trigger-based supervised classification Chapter 8 Machine learning for security boosting in Internet of Things environments Chapter 9 Combined machine learning for anomaly detection in IoT aggregator Rpi Chapter 10 Efficient intrusion detection with XGBoost and feature selection Chapter 11 A monitoring system with deep learning for IoT smart dnvironments security Chapter 12 An intrusion detection system using paragraph vector-distributed memory approach Chapter 13 Advanced security of blockchain authentication system using zero-knowledge protocol Chapter 14 Intelligent phishing URL Classification using CNN Chapter 15 The impact of AI and automation on digital forensic investigations Chapter 16 The impact of ChatGPT on cybersecurity: Balancing Benefits against Risks Chapter 17 Design of an unpredictable secure PRNG using collaborative linear feedback shift registers Chapter 18 Building trust with blockchain: Exploring its diverse applications Chapter 19 ML-based detection of GPS jamming attacks on un-manned aerial vehicles Chapter 20 A comparative analysis of random forest and isolation forest intrusion detection systems Chapter 21 A collaborative anomaly detection model using QRNN and blockchain Chapter 22 Iterated greedy with tabu search solving flow shop scheduling problem
About the Author :
Prof. Mourade Azrour received his PhD from Faculty of sciences and Techniques, Moulay Ismail University of Meknes, Morocco. He has received his MS in computer and distributed systems from Faculty of Sciences, Ibn Zouhr University, Agadir, Morocco in 2014. Mourade currently works as computer sciences professor at the Department of Computer Science, Faculty of Sciences and Techniques, Moulay Ismail University of Meknès. His research interests include Authentication protocol, Computer Security, Internet of things, Smart systems, Machine learning and so ones. Mourade is member of the scientific committee of numerous international conferences. He is also a reviewer of various scientific journals. He has published more than 120 scientific papers and book chapters. Mourade Has edited various scientific books such as “IoT and Smart Devices for Sustainable Environment” and “Advanced Technology for Smart Environment and Energy”. Finally, he has served as guest editor in journals “EAI Endorsed Transactions on Internet of Things”, “Tsinghua Science and Technology”, “Applied Sciences MDPI” and “Sustainability MDPI”
Prof. Jamal Mabrouki received his PhD in Process and Environmental Engineering at Mohammed V University in Rabat, specializing in artificial intelligence and smart automatic systems. He completed the Bachelor of Science in Physics and Chemistry with honors from Hassan II University in Casablanca, Morocco and the engineer in Environment and smart system. His research is on intelligent monitoring, control, and management systems and more particularly on sensing and supervising remote intoxication systems, smart self-supervised systems and recurrent neural networks. He has published several papers in conferences and indexed journals, most of them related to artificial intelligent systems, internet of things or big data and mining. Jamal will currently work in environment, energy and smart system professor at Mohammed V University in Rabat, Faculty of Science. Jamal is scientific committee member of numerous national and international conferences. He is also a reviewer of Modeling Earth Systems and Environment; International Journal of Environmental Analytical Chemistry; International Journal of Modeling, Simulation, and Scientific Computing; The Journal of Supercomputing, Energy & Environment and Big Data Mining and Analytics.
