Leveraging n-gram neural embeddings to improve deep learning DGA detection-Reference-Cited by-同舟云学术

Leveraging n-gram neural embeddings to improve deep learning DGA detection

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
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Author:

Morbidoni Christian¹,Spalazzi Luca²,Teti Antonio¹,Cucchiarelli Alessandro²

Affiliation:

1. Università degli Studi G. d'Annunzio, Pescara, Italy

2. Università Politecnica delle Marche, Ancona, Italy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477314.3507269

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3. A.J. Aviv and A. Haeberlen . 2011 . Challenges in Experimenting with Botnet Detection Systems. In 4th Workshop on Cyber Security Experimentation and Test, CSET 2011 (CSET'11) . USENIX Association, USA, 6. A.J. Aviv and A. Haeberlen. 2011. Challenges in Experimenting with Botnet Detection Systems. In 4th Workshop on Cyber Security Experimentation and Test, CSET 2011 (CSET'11). USENIX Association, USA, 6.

4. Detecting Domain Generation Algorithms Based on Reinforcement Learning

5. Algorithmically generated malicious domain names detection based on n-grams features

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