An optimized approach for detecting ddos attacks in iot using application networks
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Date
2022
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Publisher
UMT Lahore
Abstract
The Internet of Things (IoT) brings new applications (such as smart homes, smart cities, smart health, and smart grid) that help traditional infrastructure to communicate with smart devices. Things are linked to the Internet, and a slew of new IoT gadgets are being developed at breakneck speed. Because these smart things are connected and capable of communicating with one another in unprotected contexts, the entire communication ecology need security solutions at various levels. With billions of such gadgets already on the market with severe vulnerabilities, there is a dangerous risk to Internet networks and even individual cyberphysical systems that are also connected to the Internet. Unlike traditional networks, IoT technology has distinct features such as varying resource limits and varied network protocol needs. The attacker uses a variety of security flaws in an IoT infrastructure to launch a Distributed Denial of Service (DDoS) attack. The rise in DDoS assaults has made it critical to handle the implications in the IoT business. This study presents an effective, SoftwareDefined Internet of Things (SD-IoT)-based architecture for providing IoT network security services. We developed a novel framework for DDoS attack Recognition in SD-IoT networks leverag- ing SD-IoT. The proposed framework is based onCountdown of Recognition of DDoS Attack (C-RDA), The framework is a dynamic and programmable solution and is deeply tested with different network parameters. The algorithms demonstrate good performance with better results through Software-Defined Networking (SDN).The C-RDA approach have 97% accuracy. Moreover, the proposed framework recognizes the attack efficiently in a minimum amount of time and with lesser CPU and memory resources consumption