Docker image for the paper: Selvi, J., Rodríguez, R. J., & Soria-Olivas, E. (2019). Detection of algorithmically generated malicious domain names using masked N-grams. Expert Systems with Applications, 124, 156-163.
The image has been uploaded to docker hub, so you can run it from there:
docker run -ti jselvi/r-masked-ngrams
You can also build it yourself if you prefer so:
docker build -t jselvi/r-masked-ngrams .
Finally, after a while, you should have the following results:
Confusion Matrix and Statistics
Reference
Prediction CLEAN MALWARE
CLEAN 12565 269
MALWARE 229 12531
Accuracy : 0.9805
95% CI : (0.9788, 0.9822)
No Information Rate : 0.5001
P-Value [Acc > NIR] : < 2e-16
Kappa : 0.9611
Mcnemar's Test P-Value : 0.08053
Sensitivity : 0.9821
Specificity : 0.9790
Pos Pred Value : 0.9790
Neg Pred Value : 0.9821
Prevalence : 0.4999
Detection Rate : 0.4909
Detection Prevalence : 0.5014
Balanced Accuracy : 0.9805
'Positive' Class : CLEAN