Tests show that the proposed transfer learning method is able to detect botnets better than semi-supervised learning method that was trained on the target ...

Jun 23, 2020 · Unsupervised transfer learning is that not only the domains of source/target domain but also the tasks of source/target domain are different.

Nov 12, 2024 · We propose transfer learning as a more effective approach for botnet detection, as it can learn from well curated source data and transfer the knowledge to a ...

The first system uses an ensemble of convolutional neural networks (CNN), whose outputs are then fed to a meta-classifier for the final prediction. The second ...

Transfer Learning Approach for Botnet Detection based on Recurrent Variational Autoencoder. Jeeyung Kim. Scientific Data Management Research Group.

Transfer Learning Approach for Botnet Detection Based on Recurrent Variational Autoencoder. Jeeyung Kim, A. Sim, Jinoh Kim, Kesheng Wu, Jaegyoon Hahm. 2020 ...

Apr 26, 2021 · We propose a novel botnet detection method, built upon Recurrent Variational Autoencoder (RVAE) that effectively captures sequential characteristics of botnet ...

Duration: 25:43
Posted: Jun 25, 2020

Apr 1, 2020 · More specifically, we propose a novel machine learning based method, named. Recurrent Variational Autoencoder (RVAE), for detecting botnets.

... Recurrent Variational Autoencoder (RVAE) that effectively captures sequential characteristics of botnet activities and devise a transfer learning framework