A Review Paper on DDoS Detection Using Machine Learning
Abstract
There is almost no place in the world today that is not connected to the internet. One of the most widely used technologies is the IOT, which allows millions of devices to be connected through the internet. As this technology grows, DoS/DDoS attacks are the most common and dangerous threats. DDoS attacks are becoming more complex and they are becoming almost impossible to detect. Distributed denial of service is a subclass of denial of service. In the order to prevent DDoS attacks, many types of research have been conducted. Machine learning and deep learning are commonly used to prevent DDoS attacks. This paper describes different attack types, such as layer attacks. In this paper, we carried out a comparative analysis of machine learning algorithms to discover and classify DDoS attacks. A study of the effectiveness of detecting DoS/DDoS attacks in networks has been conducted.
References
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