Towards a machine learning-based framework for DDOS attack detection in software-defined IoT (SD-IoT) networks

National University of Computer and Emerging Sciences · Birmingham City University · +2 more institutions

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Abstract

The Internet of Things (IoT) is a complex and diverse network consisting of resource-constrained sensors/devices/things that are vulnerable to various security threats, particularly Distributed Denial of Services (DDoS) attacks. Recently, the integration of Software Defined Networking (SDN) with IoT has emerged as a promising approach for improving security and access control mechanisms. However, DDoS attacks continue to pose a significant threat to IoT networks, as they can be executed through botnet or zombie attacks. Machine learning-based security frameworks offer a viable solution to scrutinize the behavior of IoT devices and compile a profile that enables the decision-making process to maintain the…

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