| Title | DDoS Attack Detection with Packet Continuity Based on LSTM Model |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Chu, Hung-Chi, Yan, Chan-You |
| Conference Name | 2021 IEEE 3rd Eurasia Conference on IOT, Communication and Engineering (ECICE) |
| Date Published | oct |
| Keywords | Conferences, DDoS, DDoS attack detection, DDoS detection, denial-of-service attack, Human Behavior, Information systems, Internet, Metrics, Packet continuity, pubcrawl, resilience, Resiliency, Time factors |
| Abstract | Most information systems rely on the Internet to provide users with various services. Distributed Denial-of-Service (DDoS) attacks are currently one of the main cyber threats, which causes the system or network disabled. To ensure that the information system can provide services for users normally, it is important to detect the occurrence of DDoS attacks quickly and accurately. Therefore, this research proposes a system based on packet continuity to detect DDoS attacks. On average, it only takes a few milliseconds to collect a certain number of consecutive packets, and then DDoS attacks can be detected. Experimental results show that the accuracy of detecting DDoS attacks based on packet continuity is higher than 99.9% and the system response time is about 5 milliseconds. |
| DOI | 10.1109/ECICE52819.2021.9645650 |
| Citation Key | chu_ddos_2021 |
DDoS Attack Detection with Packet Continuity Based on LSTM Model