Multi-granularity Android malware fast detection based on opcode
The detection method based on opcode is widely used in Android malware detection,but it still contains some problems such as complex feature extraction method and low efficiency.In order to solve these problems,a multi-granularity fast detection method based on opcode for Android malware was propose...
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2019-12-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019064 |
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| _version_ | 1841529993069330432 |
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| author | Xuetao ZHANG Meng SUN Jinshuang WANG |
| author_facet | Xuetao ZHANG Meng SUN Jinshuang WANG |
| author_sort | Xuetao ZHANG |
| collection | DOAJ |
| description | The detection method based on opcode is widely used in Android malware detection,but it still contains some problems such as complex feature extraction method and low efficiency.In order to solve these problems,a multi-granularity fast detection method based on opcode for Android malware was proposed.Multi-granularity refers to the feature based on the bag of words model,and with the function as basic unit to extract features.By step-by-level aggregation feature,the APK multi-level information is obtained.The log length characterizes the scale of the function.And feature can be compressed and mapped to improve the efficiency and construct the corresponding classification model based on the semantic similarity of the Dalvik instruction set.Tests show that the proposed method has obvious advantages in performance and efficiency. |
| format | Article |
| id | doaj-art-a8ea4c002f3b4af78742e890b950b3ba |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2019-12-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-a8ea4c002f3b4af78742e890b950b3ba2025-01-15T03:13:51ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2019-12-015859459557134Multi-granularity Android malware fast detection based on opcodeXuetao ZHANGMeng SUNJinshuang WANGThe detection method based on opcode is widely used in Android malware detection,but it still contains some problems such as complex feature extraction method and low efficiency.In order to solve these problems,a multi-granularity fast detection method based on opcode for Android malware was proposed.Multi-granularity refers to the feature based on the bag of words model,and with the function as basic unit to extract features.By step-by-level aggregation feature,the APK multi-level information is obtained.The log length characterizes the scale of the function.And feature can be compressed and mapped to improve the efficiency and construct the corresponding classification model based on the semantic similarity of the Dalvik instruction set.Tests show that the proposed method has obvious advantages in performance and efficiency.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019064opcodecompression mapmulti-granularityrapid detectionconvolutional neural networks |
| spellingShingle | Xuetao ZHANG Meng SUN Jinshuang WANG Multi-granularity Android malware fast detection based on opcode 网络与信息安全学报 opcode compression map multi-granularity rapid detection convolutional neural networks |
| title | Multi-granularity Android malware fast detection based on opcode |
| title_full | Multi-granularity Android malware fast detection based on opcode |
| title_fullStr | Multi-granularity Android malware fast detection based on opcode |
| title_full_unstemmed | Multi-granularity Android malware fast detection based on opcode |
| title_short | Multi-granularity Android malware fast detection based on opcode |
| title_sort | multi granularity android malware fast detection based on opcode |
| topic | opcode compression map multi-granularity rapid detection convolutional neural networks |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019064 |
| work_keys_str_mv | AT xuetaozhang multigranularityandroidmalwarefastdetectionbasedonopcode AT mengsun multigranularityandroidmalwarefastdetectionbasedonopcode AT jinshuangwang multigranularityandroidmalwarefastdetectionbasedonopcode |