DDoS attack detection by using packet sampling and flow features
Jae-Hyun Jun, Cheol-Woong Ahn, Sung‐Ho Kim · 2014
DDoS attack becomes a challenge to the security of the Internet. The DDoS attack, which consumes a lot of valuable computing of communication resources, is known hard to defend. Aiming to the threat caused by DDoS attacks, current network requires an effective detection method. Therefore, an intrusion detection system on large network is needed for real-time detection. In this paper, we propose detection mechanism system by using packet sampling and flow feature against DDoS attacks in order to guarantee the transmission of normal traffic and prevent the flood of abnormal traffic. Our approach is proved to be efficiency by OPNET simulation results.