Mobile malware traffic detection approach based on value-derivative GRU
For the dramatic increase in the number and variety of mobile malware had created enormous challenge for information security of mobile network users,a value-derivative GRU-based mobile malware traffic detection approach was proposed in order to solve the problem that it was difficult for a RNN-base...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2020-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020005/ |
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| _version_ | 1841539344017391616 |
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| author | Hanxun ZHOU Chen CHEN Runze FENG Junkun XIONG Hong PAN Wei GUO |
| author_facet | Hanxun ZHOU Chen CHEN Runze FENG Junkun XIONG Hong PAN Wei GUO |
| author_sort | Hanxun ZHOU |
| collection | DOAJ |
| description | For the dramatic increase in the number and variety of mobile malware had created enormous challenge for information security of mobile network users,a value-derivative GRU-based mobile malware traffic detection approach was proposed in order to solve the problem that it was difficult for a RNN-based mobile malware traffic detection approach to capture the dynamic changes and critical information of abnormal network traffic.The low-order and high-order dynamic change information of the malicious network traffic could be described by the value-derivative GRU approach at the same time by introducing the concept of “accumulated state change”.In addition,a pooling layer could ensure that the algorithm can capture key information of malicious traffic.Finally,simulation were performed to verify the effect of accumulated state changes,hidden layers,and pooling layers on the performance of the value-derivative GRU algorithm.Experiments show that the mobile malware traffic detection approach based on value-derivative GRU has high detection accuracy. |
| format | Article |
| id | doaj-art-4a0ff49d2b294825acb7ec04f1a9719c |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2020-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-4a0ff49d2b294825acb7ec04f1a9719c2025-01-14T07:18:24ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2020-01-014110211359732617Mobile malware traffic detection approach based on value-derivative GRUHanxun ZHOUChen CHENRunze FENGJunkun XIONGHong PANWei GUOFor the dramatic increase in the number and variety of mobile malware had created enormous challenge for information security of mobile network users,a value-derivative GRU-based mobile malware traffic detection approach was proposed in order to solve the problem that it was difficult for a RNN-based mobile malware traffic detection approach to capture the dynamic changes and critical information of abnormal network traffic.The low-order and high-order dynamic change information of the malicious network traffic could be described by the value-derivative GRU approach at the same time by introducing the concept of “accumulated state change”.In addition,a pooling layer could ensure that the algorithm can capture key information of malicious traffic.Finally,simulation were performed to verify the effect of accumulated state changes,hidden layers,and pooling layers on the performance of the value-derivative GRU algorithm.Experiments show that the mobile malware traffic detection approach based on value-derivative GRU has high detection accuracy.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020005/network securitymobile malwareRNNvalue-derivative GRUtraffic detection |
| spellingShingle | Hanxun ZHOU Chen CHEN Runze FENG Junkun XIONG Hong PAN Wei GUO Mobile malware traffic detection approach based on value-derivative GRU Tongxin xuebao network security mobile malware RNN value-derivative GRU traffic detection |
| title | Mobile malware traffic detection approach based on value-derivative GRU |
| title_full | Mobile malware traffic detection approach based on value-derivative GRU |
| title_fullStr | Mobile malware traffic detection approach based on value-derivative GRU |
| title_full_unstemmed | Mobile malware traffic detection approach based on value-derivative GRU |
| title_short | Mobile malware traffic detection approach based on value-derivative GRU |
| title_sort | mobile malware traffic detection approach based on value derivative gru |
| topic | network security mobile malware RNN value-derivative GRU traffic detection |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020005/ |
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