Transfer Learning Approach for Botnet Detection Based on Recurrent Variational Autoencoder-Reference-Cited by-同舟云学术

Transfer Learning Approach for Botnet Detection Based on Recurrent Variational Autoencoder

Published:2020-06-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd International Workshop on Systems and Network Telemetry and Analytics
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Author:

Kim Jeeyung¹,Sim Alex¹,Kim Jinoh²,Wu Kesheng¹,Hahm Jaegyoon³

Affiliation:

1. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

2. Texas A&M University, Commerce, TX, USA

3. KISTI, Daejeon, South Korea

Funder

Korea Institute of Science and Technology Information (KISTI)

the Office of Advanced Scientific Computing Research Office of Science of the U.S. Department of Energy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3391812.3396273

Reference35 articles.

1. Basil Alothman. 2018. Similarity-Based Instance Transfer Learning for Botnet Detection. Basil Alothman. 2018. Similarity-Based Instance Transfer Learning for Botnet Detection.

2. J Andrews Thomas Tanay Edward J Morton and Lewis D Griffin. 2016. Transfer representation-learning for anomaly detection. JMLR. J Andrews Thomas Tanay Edward J Morton and Lewis D Griffin. 2016. Transfer representation-learning for anomaly detection. JMLR.

3. Towards effective feature selection in machine learning-based botnet detection approaches

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