engleski

Classification Based Machine Learning for Detection of DDoS attack in Cloud Computing

Distributed Denial of service attack(DDoS)is a network security attack and now the attackers intruded into almost every technology such as cloud computing, IoT, and edge computing to make themselves stronger. As per the behaviour of DDoS, all the available resources like memory, CPU or maybe the entire network are consumed by the attacker in order to shut down the victim‘s machine or server. Though plenty of defensive mechanisms are proposed, they are not efficient as the attackers get themselves trained by the newly available automated attacking tools. Therefore, we proposed a classification based machine learning approach for the detection of DDoS attack in cloud computing. With the help of three classification machine learning algorithms K Nearest Neighbor, Random Forest and Naive Bayes, the mechanism can detect a DDoS attack with an accuracy of 99.76%.

Classification ; Based Machine Learning ; Detection ; DDoS ; Attack ; Cloud Computing

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