Analysis of DDoS Attacks using Datamining
Seadon Kinny, Bijith B Maman, Walter Mhapsekar, Sarthak Waghmare, M. Kiruthika · 2023
Recent technological advancements have ushered in an era characterized by the continuous generation, processing, and sharing of huge amounts of data globally. This has significantly enhanced communication and connectivity through various devices such as Personal Computers, mobile phones, apps, and websites. With the escalating number of users, the corresponding increase in data production has resulted in a surge in internet traffic, giving rise to numerous challenges. One prominent challenge is the threat of Distributed Denial of Service (DDoS) attacks, wherein malicious actors can disturb the normal flow of traffic to a targeted server, service, or network by inundating it with a deluge of Internet traffic. In this paper a system is proposed that employs data mining techniques to analyze packet header files and identify DDoS attacks, specifically focusing on SYN flood attacks.