A Novel Machine Learning system to control Denial-of-Services Attacks - Syeda Asfiya Sabahath, Ruhiat Sultana, Syeda Meraj Bilfagih, (Design Engineering, 2021)
Denial-Of-Service (DoS) is an attack targeted at depriving legitimate users from online services. Focus to develop an algorithm which can identify whether requested service is from real user or denial of service attacks. Our proposed method uses machine learning to detect denial of service attacks by analysing the packets sent from the client to the server. For training, our algorithm gathered various datasets of benign network traffic and various forms of denial of service attacks, such as DDoS, DoS Hulk, DoS GoldenEye, DoS Slowhttptest, and DoS Slowloris. Furthermore, to detect denial of service attacks need scanning of network continuously so as dose the algorithm. For benign cases, the proposed method can differentiate between different forms of denial of service attacks, according to our findings. Furthermore, the findings could achieve a 99 percent accuracy rate in correctly classifying all of the events.