Traffic analysis for 5G network slice based on machine learning
Feng Xie, Dongxue Wei, Zhencheng Wang
Abstract
Abstract With the rise of 5G and Internet of things, especially the key technology of 5G, network slice cuts a physical network into multiple virtual end-to-end networks, each of them can obtain logically independent network resources to support richer services. 5G mobile data and sensor data converge to form a growing network traffic. Traffic explosion evolved into a mixed network type, and network viruses, worms, network theft and malicious attacks are also involved. How to distinguish traffic types, block malicious traffic and make effective use of sensor data under the background of 5G network slice, and also the significance of this study.
Topics & Concepts
Computer scienceComputer networkKey (lock)Block (permutation group theory)Cellular networkNetwork traffic controlTraffic classificationComputer securityNetwork packetMathematicsGeometryNetwork Security and Intrusion DetectionAdvanced Data and IoT TechnologiesSoftware-Defined Networks and 5G