Android malware detection method based on combined algorithm
In order to solve the problems in applicability and usability of today's static malware detection method, a detection system was implemented by using the optimal classifier selected by a combined algorithm as the core. Firstly, the reverse engineering was used to extract the software feature, t...
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| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2016-10-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016253/ |
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| _version_ | 1841529942128459776 |
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| author | Hao CHEN Sihan QING |
| author_facet | Hao CHEN Sihan QING |
| author_sort | Hao CHEN |
| collection | DOAJ |
| description | In order to solve the problems in applicability and usability of today's static malware detection method, a detection system was implemented by using the optimal classifier selected by a combined algorithm as the core. Firstly, the reverse engineering was used to extract the software feature, then the preliminary results of the classifier was got by multi-stage screening. A classifier evaluation was presented based on minimum risk Bayes. Using the new one as the core, the optimal classifier results was got by assignment. Finally, an Android malware detection system prototype was realized using the optimal results as the core. Experimental results show that the analysis accuracy of the proposed detection system was 86.4%, and does not depend on characteristics of the malicious code. |
| format | Article |
| id | doaj-art-17a2848ce8d14db796dd65040bf25733 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2016-10-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-17a2848ce8d14db796dd65040bf257332025-01-15T03:14:14ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012016-10-0132152159606924Android malware detection method based on combined algorithmHao CHENSihan QINGIn order to solve the problems in applicability and usability of today's static malware detection method, a detection system was implemented by using the optimal classifier selected by a combined algorithm as the core. Firstly, the reverse engineering was used to extract the software feature, then the preliminary results of the classifier was got by multi-stage screening. A classifier evaluation was presented based on minimum risk Bayes. Using the new one as the core, the optimal classifier results was got by assignment. Finally, an Android malware detection system prototype was realized using the optimal results as the core. Experimental results show that the analysis accuracy of the proposed detection system was 86.4%, and does not depend on characteristics of the malicious code.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016253/malware detectionfeature selectioncombined algorithmminimum risk Bayes evaluationdangerous permission combination |
| spellingShingle | Hao CHEN Sihan QING Android malware detection method based on combined algorithm Dianxin kexue malware detection feature selection combined algorithm minimum risk Bayes evaluation dangerous permission combination |
| title | Android malware detection method based on combined algorithm |
| title_full | Android malware detection method based on combined algorithm |
| title_fullStr | Android malware detection method based on combined algorithm |
| title_full_unstemmed | Android malware detection method based on combined algorithm |
| title_short | Android malware detection method based on combined algorithm |
| title_sort | android malware detection method based on combined algorithm |
| topic | malware detection feature selection combined algorithm minimum risk Bayes evaluation dangerous permission combination |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016253/ |
| work_keys_str_mv | AT haochen androidmalwaredetectionmethodbasedoncombinedalgorithm AT sihanqing androidmalwaredetectionmethodbasedoncombinedalgorithm |