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Authors: Siqi Huang ; Bo Yan and Dongmei Zhang

Affiliation: Beijing University of Posts and Telecommunications, China

Keyword(s): Domain name detection, Multi-head attention mechanism, PCFG model.

Abstract: DGA (domain generation algorithms) domain names are a class of domain names generated by specific algorithms which are used to communicate with malicious C&C servers. DGA based on the PCFG model has been proposed Lately. Under the test of existing DGA detection techniques, its anti-detection effect is very obvious. One of the reasons is that these domains are generated by legal domain names and have the same statistical characteristics of legitimate domain names. This paper proposes a detection model which combines deep learning and Multi-head attention mechanism. It employs these two techniques to extract the features of the domain names. Experiment results show that the model has a good effect on detecting domain names based on PCFG model.

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Paper citation in several formats:
Huang, S.; Yan, B. and Zhang, D. (2019). A Detection Algorithm of Malicious Domain Based on Deep Learning and Multi-Head Attention Mechanism. In Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - CTISC; ISBN 978-989-758-357-5, SciTePress, pages 84-91. DOI: 10.5220/0008098200840091

@conference{ctisc19,
author={Siqi Huang. and Bo Yan. and Dongmei Zhang.},
title={A Detection Algorithm of Malicious Domain Based on Deep Learning and Multi-Head Attention Mechanism},
booktitle={Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - CTISC},
year={2019},
pages={84-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008098200840091},
isbn={978-989-758-357-5},
}

TY - CONF

JO - Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - CTISC
TI - A Detection Algorithm of Malicious Domain Based on Deep Learning and Multi-Head Attention Mechanism
SN - 978-989-758-357-5
AU - Huang, S.
AU - Yan, B.
AU - Zhang, D.
PY - 2019
SP - 84
EP - 91
DO - 10.5220/0008098200840091
PB - SciTePress