Networks Attack Detection on 5G Networks using Data Mining Techniques (eBook, ePUB)

Redaktion: Pande, Sagar Dhanraj; Khamparia, Aditya

• Format: ePub

Produktbeschreibung

Artificial intelligence (AI) and its applications have risen to prominence as one of the most active study areas in recent years. In recent years, a rising number of AI applications have been applied in a variety of areas. Agriculture, transportation, medicine, and health are all being transformed by AI technology. The Internet of Things (IoT) market is thriving, having a significant impact on a wide variety of industries and applications, including e-health care, smart cities, smart transportation, and industrial engineering. Recent breakthroughs in artificial intelligence and machine learning techniques have reshaped various aspects of artificial vision, considerably improving the state of the art for artificial vision systems across a broad range of high-level tasks. As a result, several innovations and studies are being conducted to improve the performance and productivity of IoT devices across multiple industries using machine learning and artificial intelligence. Security is a primary consideration when analyzing the next generation communication network due to the rapid advancement of technology. Additionally, data analytics, deep intelligence, deep learning, cloud computing, and intelligent solutions are being employed in medical, agricultural, industrial, and health care systems that are based on the Internet of Things. This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods.

This book:

• Covers emerging technologies of network attacks and management aspects
• Presents artificial intelligence techniques for networks and resource optimization, and toward network automation, and security
• Showcases recent industrial and technological aspects of next-generation networks
• Illustrates artificial intelligence techniques to mitigate cyber-attacks, authentication, and authorization challenges
• Explains smart, and real-time monitoring services, multimedia, cloud computing, and information processing methodologies in 5G networks
• It is primarily for senior undergraduates, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 240
• Erscheinungstermin: 23. April 2024
• Englisch
• ISBN-13: 9781040016541
• Artikelnr.: 70258010

Autorenporträt

Dr. Sagar Dhanraj Pande Assistant Professor, Department of Computer Science and Engineering, School of Engineering and Technology, Pimpri Chinchwad University (PCU), Pune, Maharashtra, India. Dr. Sagar Dhanraj Pande has expertise in Teaching, Innovation, Research & Development of more than 8 years. He has received his Ph.D. in Computer Science and Engineering from Lovely Professional University, Phagwara, Punjab, India in 2021. He was 2nd University Topper during his Master of Engineering in 2016 at Sant Gadge Baba Amravati University, Amravati, Maharashtra, India. He has been awarded with "BEST PAPER AWARD" in 2023 from International Knowledge Research Foundation in collaboration with Eminent College of Management and Technology (ECMT), West Bengal, India. He has received the "Young Researcher Award" and "Best Ph.D. Thesis Award" in 2022 from Universal Innovators, New Delhi, India. Also, he has received the "Emerging Scientist Award" in 2021 from VDGOOD Professional Association, Pondicherry, India. He has been Session Chair of Multiple International Conferences. His research interest is Deep Learning, Machine Learning, Network Attacks, Cyber Security, and the Internet of Medical Things (IoMT). He has published and presented more than 85 papers in IEEE, Springer, Elsevier, Taylor & Francis, and other reputable journals which are SCI, SCIE, Scopus indexed & peer-review journals. Also, he has published more than 48 Patents on the topics of Computer Vision, Natural Language Processing, Generative AI, IoT, and its applications. He is currently supervising 4 Ph. D Scholar in the domain of AIML. He has also supervised several postgraduate students in cybersecurity, computer networks, and AI. He is responsible for teaching Artificial Intelligence, Deep Learning, Machine Learning, Cyber Crime and Security, and Python Programming courses to undergraduate and post- graduate students. He is also sharing his knowledge through his YouTube channel named sdpguruj https://www.youtube.com/c/SDPGuruji/playlists. Dr. Aditya Khamparia Assistant Professor, Coordinator of Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. Dr. Aditya Khamparia has expertise in Teaching, Entrepreneurship, and Research & Development of 8 years. He is currently working as Assistant Professor and Coordinator of Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab in May 2018. He has completed his M. Tech. from VIT University and B. Tech. from RGPV, Bhopal. He has completed his PDF from UNIFOR, Brazil. He has around 95 research papers along with book chapters including more than 15 papers in SCI indexed Journals with cumulative impact factor of above 50 to his credit. Additionally, He has authored, edited and editing 5 books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/ Guest Editor and many more positions in various conferences and journals. His research interest includes machine learning, deep learning, educational technologies, computer vision.

Inhaltsangabe

1. Enhancing 5G and IoT Network Security: A Multi-Model Deep Learning
Approach for Attack Classification. 2. Dynamic Deployment and Traffic
Scheduling of UPF in 5G Networks. 3. Spatial Federated Learning and
Blockchain based 5G Communication Model for Hiding Confidential
Information. 4. Mining Intelligence Hierarchical Feature for Malware
Detection over 5G Network. 5. Enhancing Reliability and Security of Power
Monitoring Systems in the Era of 5G Networks. 6. Passive Voice in 5G Mobile
Edge Computing: Optimizing Energy Efficiency and Resource Utilization. 7.
Exchange Matching Algorithm for Low-Complexity Traffic Scheduling for 5G
Fronthaul Networks. 8. Attack Path Discovery in Dynamic Network
Environments for Automated Penetration Testing over 5G Networks. 9.
Enhancing Electric Vehicle Charging Efficiency in Urban Areas with 5G
Network Integration and Network Attack Mitigation. 10. Next-Generation
Intrusion Detection System for 5G Networks with Enhanced Security Using
Updated Datasets