Chargement en cours...
Unsupervised, low latency anomaly detection of algorithmically generated domain names by generative probabilistic modeling
We propose a method for detecting anomalous domain names, with focus on algorithmically generated domain names which are frequently associated with malicious activities such as fast flux service networks, particularly for bot networks (or botnets), malware, and phishing. Our method is based on learn...
Enregistré dans:
| Publié dans: | J Adv Res |
|---|---|
| Auteurs principaux: | , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Elsevier
2014
|
| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4294760/ https://ncbi.nlm.nih.gov/pubmed/25685511 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jare.2014.01.001 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|