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Malware Detection Based on Multidimensional Time Distribution Features

Huizhong Sun1, Guosheng Xu1,*, Hewei Yu2, Minyan Ma3, Yanhui Guo1, Ruijie Quan4

1 School of Cyberspace Security, Beijing University of Posts and Telecommunication, Beijing, China
2 Computer Network Emergency Response Technical Team/Coordination Center of China (CNCERT/CC), Beijing, China
3 Zhejiang Branch of National Computer Network Emergency Response Technical Team/Coordination Center of China, Hangzhou, China
4 Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia

* Corresponding Author: Guosheng Xu. Email: email

Journal of Quantum Computing 2021, 3(2), 55-63. https://doi.org/10.32604/jqc.2021.017365

Abstract

Language detection models based on system calls suffer from certain false negatives and detection blind spots. Hence, the normal behavior sequences of some malware applications for a short period can become malicious behavior within a certain time window. To detect such behaviors, we extract a multidimensional time distribution feature matrix on the basis of statistical analysis. This matrix mainly includes multidimensional time distribution features, multidimensional word pair correlation features, and multidimensional word frequency distribution features. A multidimensional time distribution model based on neural networks is built to detect the overall abnormal behavior within a given time window. Experimental evaluation is conducted using the ADFA-LD dataset. Accuracy, precision, and recall are used as the measurement indicators of the model. An accuracy rate of 95.26% and a recall rate of 96.11% are achieved.

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APA Style
Sun, H., Xu, G., Yu, H., Ma, M., Guo, Y. et al. (2021). Malware detection based on multidimensional time distribution features. Journal of Quantum Computing, 3(2), 55-63. https://doi.org/10.32604/jqc.2021.017365
Vancouver Style
Sun H, Xu G, Yu H, Ma M, Guo Y, Quan R. Malware detection based on multidimensional time distribution features. J Quantum Comput . 2021;3(2):55-63 https://doi.org/10.32604/jqc.2021.017365
IEEE Style
H. Sun, G. Xu, H. Yu, M. Ma, Y. Guo, and R. Quan "Malware Detection Based on Multidimensional Time Distribution Features," J. Quantum Comput. , vol. 3, no. 2, pp. 55-63. 2021. https://doi.org/10.32604/jqc.2021.017365



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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