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Title	Ddos Detection At Fog Layer In Internet Of Things
ID_Doc	17578
Authors	Dave S.; Degadwala S.; Vyas D.
Year	2022
Published	International Conference on Edge Computing and Applications, ICECAA 2022 - Proceedings
DOI	http://dx.doi.org/10.1109/ICECAA55415.2022.9936524
Abstract	The Internet of Things (IoT) is a quite recent technology thathas emerged in recent years. It enables the progression of a diverse wide variety of new venture application options (e.g., wearables, smarthomes, smart cities, etc.). However, there are issues with IoT security measures that must be handled in order to maintain a secure connection. In recent years, distributed denial of service (DDOS) attacks has emerged as significant danger to the Internet of Things network. DDoS attacks deplete the resources available to IoTend devices, such as storage and network bandwidth, resulting in difficulties with IoT applications. This study's goal is to develop an effective DDoS detection framework for IoTenvironments in the fog layer. The framework uses two types of techniques to deal with both known and unknown attacks. They are signature-based and machine learning-based anomaly detection techniques. Fog computing enables the mitigation framework to be resource efficient. © 2022 IEEE.
Author Keywords	Anomaly Detection; Distributed Denial of Service (DDoS); Fog Layer; Internet of Things (IoT); Machine Learning algorithm

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