Detecting Malware Using Graph Embedding and DNN

Rui Wang, Jun Zheng, Zhiwei Shi, Yu'an Tan

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Nowadays, the popularity of intelligent terminals makes malwares more and more serious. Among the many features of application, the call graph can accurately express the behavior of the application. The rapid development of graph neural network in recent years provides a new solution for the malicious analysis of application using call graphs as features. However, there are still problems such as low accuracy. This paper established a large-scale data set containing more than 40,000 samples and selected the class call graph, which was extracted from the application, as the feature and used the graph embedding combined with the deep neural network to detect the malware. The experimental results show that the accuracy of the detection model proposed in this paper is 97.7%; the precision is 96.6%; the recall is 96.8%; the F1-score is 96.4%, which is better than the existing detection model based on Markov chain and graph embedding detection model.

源语言英语
主期刊名Proceedings - 2022 International Conference on Blockchain Technology and Information Security, ICBCTIS 2022
出版商Institute of Electrical and Electronics Engineers Inc.
28-31
页数4
ISBN(电子版)9781665496919
DOI
出版状态已出版 - 2022
活动2022 International Conference on Blockchain Technology and Information Security, ICBCTIS 2022 - Huaihua City, 中国
期限: 15 7月 202217 7月 2022

出版系列

姓名Proceedings - 2022 International Conference on Blockchain Technology and Information Security, ICBCTIS 2022

会议

会议2022 International Conference on Blockchain Technology and Information Security, ICBCTIS 2022
国家/地区中国
Huaihua City
时期15/07/2217/07/22

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引用此

Wang, R., Zheng, J., Shi, Z., & Tan, Y. (2022). Detecting Malware Using Graph Embedding and DNN. 在 Proceedings - 2022 International Conference on Blockchain Technology and Information Security, ICBCTIS 2022 (页码 28-31). (Proceedings - 2022 International Conference on Blockchain Technology and Information Security, ICBCTIS 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICBCTIS55569.2022.00018