Android malware detection method based on deep neural network
Android is increasingly facing the threat of malware attacks.It is difficult to effectively detect large-sample and multi-class malware for traditional machine learning methods such as support vector machine,method for Android malware detection and family classification based on deep neural network...
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Format: | Article |
Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2020-10-01
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Series: | 网络与信息安全学报 |
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Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020060 |
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author | Fan CHAO Zhi YANG Xuehui DU Yan SUN |
author_facet | Fan CHAO Zhi YANG Xuehui DU Yan SUN |
author_sort | Fan CHAO |
collection | DOAJ |
description | Android is increasingly facing the threat of malware attacks.It is difficult to effectively detect large-sample and multi-class malware for traditional machine learning methods such as support vector machine,method for Android malware detection and family classification based on deep neural network was proposed.Based on the comprehensive extraction of application components,Intent Filter,permissions,and data flow,the method performed an effective feature selection to reduce dimensions,and conducted a large-sample detection and multi-class classification for malware based on deep neural network.The experimental results show that the method can conduct an effective detection and classification.The accuracy of binary classification between benign and malicious Apps is 97.73%,and the accuracy of family multi-class classification can reach 93.54%,which is higher than other machine learning algorithms. |
format | Article |
id | doaj-art-7576abc5627740b39bab4ffa966107e0 |
institution | Kabale University |
issn | 2096-109X |
language | English |
publishDate | 2020-10-01 |
publisher | POSTS&TELECOM PRESS Co., LTD |
record_format | Article |
series | 网络与信息安全学报 |
spelling | doaj-art-7576abc5627740b39bab4ffa966107e02025-01-15T03:14:23ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2020-10-016677959560964Android malware detection method based on deep neural networkFan CHAOZhi YANGXuehui DUYan SUNAndroid is increasingly facing the threat of malware attacks.It is difficult to effectively detect large-sample and multi-class malware for traditional machine learning methods such as support vector machine,method for Android malware detection and family classification based on deep neural network was proposed.Based on the comprehensive extraction of application components,Intent Filter,permissions,and data flow,the method performed an effective feature selection to reduce dimensions,and conducted a large-sample detection and multi-class classification for malware based on deep neural network.The experimental results show that the method can conduct an effective detection and classification.The accuracy of binary classification between benign and malicious Apps is 97.73%,and the accuracy of family multi-class classification can reach 93.54%,which is higher than other machine learning algorithms.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020060Androidmalware detectionstatic analysisfeature selectiondeep neural network |
spellingShingle | Fan CHAO Zhi YANG Xuehui DU Yan SUN Android malware detection method based on deep neural network 网络与信息安全学报 Android malware detection static analysis feature selection deep neural network |
title | Android malware detection method based on deep neural network |
title_full | Android malware detection method based on deep neural network |
title_fullStr | Android malware detection method based on deep neural network |
title_full_unstemmed | Android malware detection method based on deep neural network |
title_short | Android malware detection method based on deep neural network |
title_sort | android malware detection method based on deep neural network |
topic | Android malware detection static analysis feature selection deep neural network |
url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020060 |
work_keys_str_mv | AT fanchao androidmalwaredetectionmethodbasedondeepneuralnetwork AT zhiyang androidmalwaredetectionmethodbasedondeepneuralnetwork AT xuehuidu androidmalwaredetectionmethodbasedondeepneuralnetwork AT yansun androidmalwaredetectionmethodbasedondeepneuralnetwork |