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23.7 MB
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FC5EB62E8E2AB688C2C1BB38FA976EE1F9162EB3
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April 20, 2026, 3:28 a.m.
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(Last updated: April 20, 2026, 3:28 a.m.)
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| ['Azrour M. Recent Advances in Internet of Things Security 2025.pdf'] | 0 bytes |
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23.7 MB
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2026-04-20
| Uploaded by andryold1 | Size 23.7 MB | Health [ 20 /43 ] | Added 2026-04-20 |
NOTE
SOURCE: Azrour M. Recent Advances in Internet of Things Security 2025
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COVER
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MEDIAINFO
Textbook in PDF format 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. Preface 1 Strengthening IIoT security: Integrating intrusion detection systems with machine learning 2 Scalable IoT anomaly detection: Federated and split learning 3 Machine learning–based detection in wireless sensor networks 4 A secure approach for next-generation IoT networks: A comparative analysis 5 Efficient ECC-based RFID authentication for enhanced IoT security 6 An AI-based embedded system for access control and absence management 7 A new perspective on E-health perforated blockchain: An intelligent healthcare revolution using trigger-based supervised classification 8 Machine learning for security boosting in Internet of Things environments 9 Combined machine learning for anomaly detection in IoT aggregator RPi 10 Efficient IoT intrusion detection with XGBoost and feature selection 11 A monitoring system with deep learning for IoT smart environments security 12 An intrusion detection system using paragraph vector-distributed memory approach 13 Advanced security of blockchain authentication system using zero-knowledge protocol 14 Intelligent phishing URL classification using CNN 15 The impact of AI and automation on digital forensic investigations 16 The impact of ChatGPT on cybersecurity: Balancing benefits against risks 17 Design of an unpredictable secure PRNG using collaborative linear feedback shift registers 18 Building trust with blockchain: Exploring its diverse applications 19 ML-based detection of GPS jamming attacks on unmanned aerial vehicles 20 A comparative analysis of random forest and isolation forest intrusion detection systems 21 A collaborative anomaly detection model using QRNN and blockchain 22 Iterated greedy with tabu search solving flow shop scheduling problem
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