2A Novel Data Offloading with Deep Learning Enabled Cyberattack Detection Model for Edge Computing in 6G Networks

Elsaid M. Abdelrahim

Department of Mathematics Computer Science Division, Faculty of Science, Tanta University, Tanta, Egypt

2.1 Introduction

Since 5G has brought vertical transformation for changing the society and progressively opened the curtain of internet of everything, 6G has opened an innovative era of “Internet of Intelligence” with connected things, intelligence, and people, resolving human problems in various aspects [1]. To authorize the 6G network using artificial intelligence (AI) abilities, massive amount of multi‐modal information (for example, user videos, behavior records, and audios) of physical environments would be generated endlessly by the Internet of Things (IoT) and mobile gadgets that reside at the network edge. Driving by this trend, there is urgency for pushing the AI frontier to the network edge for completely unleashing the 6G network [2]. To satisfy the user need, edge computing, an emergent model that drives computational services and tasks from the network core to the network edge, was extensively known as essential component for the forthcoming 6G network. Mobile edge computing (MEC) is an alternative transmission system that provides service to users. This tool facilitates a mobile computing model with autonomous server and function that is attained from IoT or cloud layers. The derivative resource is extended for users to provide ...

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