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Authors: Aimen Mahmood 1 ; Haider Abbas 2 and Faisal Amjad 1

Affiliations: 1 National University of Sciences and Technology, Islamabad, Pakistan ; 2 KTH-Royal Institute of Technology, Stockholm, Sweden

Keyword(s): Domain Generation Algorithms, Domain Fluxing, Classification of DGA, Word-List DGA, Pseudo Random DGA, Convolution Neural Network.

Abstract: To remotely control the target machine, hackers manage to establish a connection between victim and their Command and Control server(C2). In order to hide their C2 they generate domain names algorithmically. Such algorithms are called Domain Generation algorithms(DGA). These algorithmically generated domain names are either gibberish as the characters are generated and concatenated randomly, or pure dictionary words or the combination of the two. This paper presents an algorithm that classifies the DGA running on a compromised system either as gibberish, dictionary oriented or the mixed one, in real time. The proposed algorithm consists of two distinct modules i) Network forensics to detect the DGA ii) Classification of the DGA using the combination of Hidden Markov Model and Convolution Neural Network in real time. The algorithm is trained and tested against more than 0.21 million samples taken from more than 50 different DGAs. The algorithm gives as good as 99% accuracy for all typ es of DGAs. In addition it can detect zero day DGA as well as multiple DGAs running on a system. (More)

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Paper citation in several formats:
Mahmood, A., Abbas, H. and Amjad, F. (2023). CNN-HMM Model for Real Time DGA Categorization. In Proceedings of the 20th International Conference on Security and Cryptography - SECRYPT; ISBN 978-989-758-666-8; ISSN 2184-7711, SciTePress, pages 822-829. DOI: 10.5220/0012136800003555

@conference{secrypt23,
author={Aimen Mahmood and Haider Abbas and Faisal Amjad},
title={CNN-HMM Model for Real Time DGA Categorization},
booktitle={Proceedings of the 20th International Conference on Security and Cryptography - SECRYPT},
year={2023},
pages={822-829},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012136800003555},
isbn={978-989-758-666-8},
issn={2184-7711},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Security and Cryptography - SECRYPT
TI - CNN-HMM Model for Real Time DGA Categorization
SN - 978-989-758-666-8
IS - 2184-7711
AU - Mahmood, A.
AU - Abbas, H.
AU - Amjad, F.
PY - 2023
SP - 822
EP - 829
DO - 10.5220/0012136800003555
PB - SciTePress

- Science and Technology Publications, Lda.
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