Detecting Strategy of Fast Flux Domain Based on Hidden Markov Model
Ren-De Huang, Shu–Yu Kuo, Yao–Hsin Chou · 網際網路技術學刊 · 2015
In modern, the network progresses rapidly. Network attacks transform from single attack to multiple attacks so that the entire network may be paralyzed. Network security has become an important issue. In this paper, we probe that Fast Flux has developed into a new attack method with the increasing of network bandwidth and speed. Undoubtedly, if attackers adopt Fast Flux, detectors will be more difficult to detect. In this paper, it uses the hidden Markov model (HMM), which is the statistical classification model, to detect the Fast Flux attacks. It is the first time to detect Fast Flux attacks by the HMM. Generally, HMM is used to process voice recognition applications because the voice data mostly are serial data. Likewise, we convert the property of the Fast Flux into the serial data. In our experiment, it is certainly an effective and reliable way to adopt the HMM to detect Fast Flux attacks.