Malicious domain name detection model based on CNN-LSTM

Jianhui Zhang; Haoyue Sun; Jiao Wang

doi:10.1117/12.2659649

28 October 2022 Malicious domain name detection model based on CNN-LSTM

Jianhui Zhang, Haoyue Sun, Jiao Wang

Proceedings Volume 12453, Third International Conference on Computer Communication and Network Security (CCNS 2022); 124530B (2022) https://doi.org/10.1117/12.2659649
Event: Third International Conference on Computer Communication and Network Security (CCNS 2022), 2022, Hohhot, China

Abstract

Botnets widely use DGA (Domain Generation Algorithm) technology to evade network security detection, and DGA malicious domain name detection has attracted much attention. Aiming at the problem that poor feature extraction effect and low detection accuracy of existing domain name detection methods, this paper proposes a hybrid neural network model based on CNN-LSTM. The model first uses multi-channel Convolutional Neural Network (CNN) to extract the NGram features of domain names; then uses Long Short-Term Memory (LSTM) to extract the contextual grammar features of domain names; finally introduces the attention mechanism to assign different weights for the extracted domain name features, focusing on more critical information. The experiment results illustrate the proposed model maintains an Accuracy of 99.02% in malicious domain name detection, which can obtain higher detection accuracy than the existing domain name detection model.

Citation Download Citation

Jianhui Zhang, Haoyue Sun, and Jiao Wang "Malicious domain name detection model based on CNN-LSTM", Proc. SPIE 12453, Third International Conference on Computer Communication and Network Security (CCNS 2022), 124530B (28 October 2022); https://doi.org/10.1117/12.2659649

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available