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Title	Ddos Attack Detection System For Iot Enabled Smart City Applications With Correlation Analysis
ID_Doc	17576
Authors	Nirosha V.; Hemamalini V.
Year	2024
Published	2024 4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024
DOI	http://dx.doi.org/10.1109/ICAECT60202.2024.10469454
Abstract	The topic of cybersecurity remains a significant concern for industries involved in digital operations, as seen by the recurring increase in security incidents. The increasing use of Internet of Things (IoT) devices in various settings such as homes, offices, transportation, and healthcare has resulted in a corresponding rise in the frequency of malicious assaults. Machine Learning (ML) is frequently utilized for the purpose of detecting attacks on IoT devices. This study presents a novel approach to cybersecurity-focused network traffic correlation analysis and the detection of Distributed Denial of Service (DDoS) attacks using artificial intelligence techniques in the context of an IoT-enabled smart city, with the aim of promoting sustainability. A traffic analysis was conducted by utilizing a wireshark network analyser tool, which effectively improves data transmission. The experimental investigation was conducted to evaluate various performance metrics, including accuracy, precision, recall, attack detection rate and time. The proposed technique achieved anaccuracy rate of 96%, precision and recall rates are 93.6% and 91% respectively. © 2024 IEEE.
Author Keywords	correlation analysis; Cyber security; DDoS attack; smart city

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