RNN-based DDoS Detection in IoT Scenario
Chun-Yu Chen, Lo-An Chen, Yun-Zhan Cai, Meng‐Hsun Tsai · 2020
With the advancement of wired and wireless communication technologies, the Internet of Things (IoT) devices are also increasing. Hackers exploit a massive amount of IoT devices, which lack security protection for specific purposes. Distributed denial of service (DDoS) attack is an enhanced denial of service (DoS) attack and is one of these hacked devices' common usages. This paper proposes a time-stamped bi-directional gated recurrent unit (GRU) model to detect DDoS attacks. Compared with previous work, our method maintains higher accuracy and lower training time. Generally, in most DDoS attack schemes, the accuracy is still high.