# Mdpi
## 4 Threats
### Obfuscated Webshell
In the case of the rapid development of threat intelligence, it is difficult to perform comprehensive detection using a detection method, which leads to the need for traditional detection methods for auxiliary analysis when detecting in a real environment. In future, traditional detection methods and machine learning detection methods can be combined to propose a more comprehensive detection method. The work of this paper nevertheless has some limitations. Webshell sample collection is difficult, and the number of sample collections was small, resulting in over-fitting of the detection model. The above questions are the next issues that need to be studied and solved. Writing--original draft, Y.G., H.M.-G., and P.K. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Authors declare no conflicts of interest. ## References

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\begin{tabular}{c c c c c c} \hline \hline
**Detector** & **Version** & **Accuracy (\%)** & **Precision (\%)** & **Recall (\%)** & **F1 Score (\%)** \\ \hline NB-Opcode & - & 97.4 & 97.2 & 96.8 & 97.0 \\ \hline Webshell Killer & V2.10 & 88.6 & 85.9 & 80.3 & 83.0 \\ \hline D-Shield & V2.1.5.2 & 92.4 & 87.9 & 90.6 & 89.2 \\ \hline Web Shell Detector & V1.1 by Python & 84.6 & 68.2 & 77.4 & 75.5 \\ \hline \hline \end{tabular}
\end{table} 
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