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Android Malware Detection Framework Based on Static Analysis
http://hdl.handle.net/20.500.12678/0000004829
http://hdl.handle.net/20.500.12678/0000004829416c4e8b-9c43-43d4-8028-1546a821e737
f04fde78-54f3-42a0-946a-1a11c9b52fa0
Publication type | ||||||
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Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Android Malware Detection Framework Based on Static Analysis | |||||
Language | en | |||||
Publication date | 2017-02-16 | |||||
Authors | ||||||
Soe, Yan Naung | ||||||
Oo, Khine Khine | ||||||
Description | ||||||
Mobile devices have gained tremendouspopularity over the last few years. The most popularusage is the smart phones. They are accepted andadmired by many mainly because they are capable ofproviding services such as banking, social network,etc all on the go. There are many operating systemsused in mobile devices. Among them, IOS andAndroid systems are the most acceptabletechnologies. Android platform is the fastest growingmarket in smart phone operating systems to date.Therefore, the malicious applications targeting theAndroid system has exploded in recent years. Theandroid malware detection framework is establishedby the static ways by analyzing the androidpermission and signature of source codes. Forsignature based detection, it is used clone detectiontechnique. For permission-based detection, it isdetected by using machine learning classifier. Bycombining with these two approach, this frameworkimproves the performance of the malware detection. | ||||||
Keywords | ||||||
Android, Malware, Mobile Security, Signature, Permission | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/729 | |||||
Journal articles | ||||||
Fifteenth International Conference on Computer Applications(ICCA 2017) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |