Blockchain and Machine Learning for IoT Security
Herausgeber: Azrour, Mourade; Guezzaz, Azidine; Mabrouki, Jamal
Blockchain and Machine Learning for IoT Security
Herausgeber: Azrour, Mourade; Guezzaz, Azidine; Mabrouki, Jamal
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This book discusses various recent techniques and solutions related to IoT deployment, especially security, and privacy. It addresses a variety of subjects, including a comprehensive overview of the IoT, and covers in detail the security challenges at each layer.
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This book discusses various recent techniques and solutions related to IoT deployment, especially security, and privacy. It addresses a variety of subjects, including a comprehensive overview of the IoT, and covers in detail the security challenges at each layer.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 152
- Erscheinungstermin: 9. Februar 2024
- Englisch
- Abmessung: 234mm x 156mm x 11mm
- Gewicht: 413g
- ISBN-13: 9781032563442
- ISBN-10: 1032563443
- Artikelnr.: 69431679
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 152
- Erscheinungstermin: 9. Februar 2024
- Englisch
- Abmessung: 234mm x 156mm x 11mm
- Gewicht: 413g
- ISBN-13: 9781032563442
- ISBN-10: 1032563443
- Artikelnr.: 69431679
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. 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. Prof. Azidine Guezzaz received his Ph.D from Ibn Zohr University Agadir, Morocco in 2018. He obtained his Master in computer and distributed systems from Faculty of Sciences, Ibn Zouhr University, Agadir, Morocco in 2013. He is currently an associate professor of computer science and mathematics at Cadi Ayyad University Marrakech, Morocco. His main field of research interest is computer security, cryptography, artificial intelligence, intrusion detection and smart cities. Prof. Said Benkirane obtained his Engineering Degree in Networks and Telecommunications in 2004 from INPT in Rabat, Morocco. He obtained his Master degree in Computer and Network Engineering in 2006 at the USMBA University of Fez and his PhD in Computer Science in 2013 at the UCD University of El-JadidaMorocco. He worked as Professor from 2014 at ESTE Cadi Ayyad University. His areas of research are Artificial Intelligence, Multi Agents, and Systems Security.
1. Google trend analysis of airport passenger throughputs: case study of
Murtala Muhammed International Airpor 2. Blockchain Technology Overview:
Architecture, proposed and Future Trends 3. Innovative Approach for
Optimized IoT Security based on Spatial Network 4. The combination of
blockchain and Internet of Things (IoT) Applications, Opportunities and
Challenges for Industry 5. Security Issues in Internet of Medical Things 6.
Intrusion detection Framework using AdaBoost algorithm and Chi-squared
technique 7. A Collaborative Intrusion Detection Approach Based on Deep
Learning and Blockchain 8. GVGB-IDS: An Intrusion Detection System using
Graphic Visualization and Gradient Boosting for cloud Monitoring 9. Design
and Implementation of Intrusion Detection Model with Machine Learning
Techniques for IoT Security
Murtala Muhammed International Airpor 2. Blockchain Technology Overview:
Architecture, proposed and Future Trends 3. Innovative Approach for
Optimized IoT Security based on Spatial Network 4. The combination of
blockchain and Internet of Things (IoT) Applications, Opportunities and
Challenges for Industry 5. Security Issues in Internet of Medical Things 6.
Intrusion detection Framework using AdaBoost algorithm and Chi-squared
technique 7. A Collaborative Intrusion Detection Approach Based on Deep
Learning and Blockchain 8. GVGB-IDS: An Intrusion Detection System using
Graphic Visualization and Gradient Boosting for cloud Monitoring 9. Design
and Implementation of Intrusion Detection Model with Machine Learning
Techniques for IoT Security
1. Google trend analysis of airport passenger throughputs: case study of
Murtala Muhammed International Airpor 2. Blockchain Technology Overview:
Architecture, proposed and Future Trends 3. Innovative Approach for
Optimized IoT Security based on Spatial Network 4. The combination of
blockchain and Internet of Things (IoT) Applications, Opportunities and
Challenges for Industry 5. Security Issues in Internet of Medical Things 6.
Intrusion detection Framework using AdaBoost algorithm and Chi-squared
technique 7. A Collaborative Intrusion Detection Approach Based on Deep
Learning and Blockchain 8. GVGB-IDS: An Intrusion Detection System using
Graphic Visualization and Gradient Boosting for cloud Monitoring 9. Design
and Implementation of Intrusion Detection Model with Machine Learning
Techniques for IoT Security
Murtala Muhammed International Airpor 2. Blockchain Technology Overview:
Architecture, proposed and Future Trends 3. Innovative Approach for
Optimized IoT Security based on Spatial Network 4. The combination of
blockchain and Internet of Things (IoT) Applications, Opportunities and
Challenges for Industry 5. Security Issues in Internet of Medical Things 6.
Intrusion detection Framework using AdaBoost algorithm and Chi-squared
technique 7. A Collaborative Intrusion Detection Approach Based on Deep
Learning and Blockchain 8. GVGB-IDS: An Intrusion Detection System using
Graphic Visualization and Gradient Boosting for cloud Monitoring 9. Design
and Implementation of Intrusion Detection Model with Machine Learning
Techniques for IoT Security