Networks Attack Detection on 5G Networks using Data Mining TechniquesКНИГИ » СЕТЕВЫЕ ТЕХНОЛОГИИ
Название: Networks Attack Detection on 5G Networks using Data Mining Techniques Автор: Sagar Dhanraj Pande, Aditya Khamparia Издательство: CRC Press Серия: Wireless Communications and Networking Technologies Год: 2024 Страниц: 216 Язык: английский Формат: pdf (true) Размер: 10.1 MB
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.
The main aim of this book is to provide a detailed understanding of Network Attacks Detection on 5G Networks assisted applications with involvement of distinct intelligent computing methods and optimized algorithms in the field of computer science. This book will also concentrate on applications utilizing Network Attacks and AI/ML in various domains/perspectives.
The successor to 4G, 5G is the next generation of mobile network technology. It offers diverse applications, including product development and high-speed data transfer. It aims to solve issues from 4G’s widespread adoption by providing wide coverage and high throughput using millimeter waves. Advanced antennas and modulation methods enable high-bandwidth bidirectional communication. 5G enables downloading full movies, potentially rendering technologies like Bluetooth obsolete. 5G smartphones are expected to resemble tablets in size and features, and security is a significant concern. These technologies enable network operators to shift toward service-focused management, improve customer service, and aid in network optimization. ML, a subset of AI, facilitates predictions based on historical data, while AI helps recover costs for network upgrades. Despite its advantages, AI introduces data challenges. Incorporating ML enhances traffic forecasting, analytics, network visibility, and security against intrusions, making AI a powerful ally in the evolving 5G landscape.
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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