Smart City Gnosys
Smart city article details
| Title | Networks Attack Detection On 5G Networks Using Data Mining Techniques |
|---|---|
| ID_Doc | 39051 |
| Authors | Pande S.D.; Khamparia A. |
| Year | 2024 |
| Published | Networks Attack Detection on 5G Networks using Data Mining Techniques |
| DOI | http://dx.doi.org/10.1201/9781003470281 |
| Abstract | 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. © 2024 selection and editorial matter, Sagar Dhanraj Pande and Aditya Khamparia; individual chapters, the contributors. |
| Author Keywords |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
33508  | 0.9 | Saini K.S.; Chaudhary S. | Investigation On Attack Detection In Iot Networks: A Study And Analysis Of The Existing Machine Learning And Deep Learning Techniques | 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025 (2025) |
| 58830 | 0.895 | Sharma N.; Shambharkar P.G. | Transforming Security In Internet Of Medical Things With Advanced Deep Learning-Based Intrusion Detection Frameworks | Applied Soft Computing, 180 (2025) |
| 10470 | 0.891 | Khan I.U.; Ouaissa M.; Ouaissa M.; Fayaz M.; Ullah R. | Artificial Intelligence For Intelligent Systems: Fundamentals, Challenges, And Applications | Artificial Intelligence for Intelligent Systems: Fundamentals, Challenges, and Applications (2024) |
| 32899 | 0.891 | Sarker I.H.; Khan A.I.; Abushark Y.B.; Alsolami F. | Internet Of Things (Iot) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions And Research Directions | Mobile Networks and Applications, 28, 1 (2023) |
| 9199 | 0.89 | Mazhar T.; Talpur D.B.; Shloul T.A.; Ghadi Y.Y.; Haq I.; Ullah I.; Ouahada K.; Hamam H. | Analysis Of Iot Security Challenges And Its Solutions Using Artificial Intelligence | Brain Sciences, 13, 4 (2023) |
| 975 | 0.882 | Khan M.A.A.; Kaidi H.M. | A Comprehensive Survey Of Machine Learning Techniques In Next-Generation Wireless Networks And The Internet Of Things | Ingenierie des Systemes d'Information, 28, 4 (2023) |
| 36080 | 0.882 | Ahanger T.A.; Ullah I.; Algamdi S.A.; Tariq U. | Machine Learning-Inspired Intrusion Detection System For Iot: Security Issues And Future Challenges | Computers and Electrical Engineering, 123 (2025) |
| 6593 | 0.88 | Rao G.S.; Yuvaraj S.A.; Kondapi N.R.; Kumari A.R.; Palepu N.R.; Bharathi C.R.; Arulananth T.S.; Ebinezer M.J.D. | Advancements In Machine Learning For Iot: Ai-Driven Optimization And Security | Journal of Information Systems Engineering and Management, 10, 17 (2025) |
| 36064 | 0.879 | Alfahaid A.; Alalwany E.; Almars A.M.; Alharbi F.; Atlam E.; Mahgoub I. | Machine Learning-Based Security Solutions For Iot Networks: A Comprehensive Survey | Sensors, 25, 11 (2025) |
| 33032 | 0.877 | Dawoud A.; Sianaki O.A.; Shahristani S.; Raun C. | Internet Of Things Intrusion Detection: A Deep Learning Approach | 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (2020) |