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  1. University of Computer Studies, Yangon
  2. Journals

Permission Based Anomalous Application Detection on Android Smart Phone

http://hdl.handle.net/20.500.12678/0000004389
http://hdl.handle.net/20.500.12678/0000004389
ca3eeccd-f96f-4bdc-ac43-fc66c39cc3ff
2d987947-350f-4db8-8ab0-96f6af76dfa8
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NJPSC NJPSC 2019 Proceedings-pages-248-255.pdf (632 Kb)
Publication type
Article
Upload type
Publication
Title
Title Permission Based Anomalous Application Detection on Android Smart Phone
Language en_US
Publication date 2019-03
Authors
Win, Htet Htet
Nway, Zon Nyein
Description
Android applications are widely used bymillions of users to perform many different activities.Android-based smart phone users can get freeapplications from Android Application Market. But,these applications were not certified by legitimateorganizations and they may contain malwareapplications that can steal private information fromusers. The proposed system develops a permissionbased malware detection to protect the privacy ofandroid smart phone users. This system monitorsvarious permissions obtained from androidapplications and analyses them by using a statisticaltechnique called singular value decomposition (SVD)to estimate the correlations of permissions. Thetraining phase emphasizes on the malware samples(approximately 300) downloaded fromhttps://www.kaggle.com/goorax/static-analysis-ofandroid-malware-of-2017. The proposed systemevaluates the risk level (High, Medium, and Low) ofAndroid applications based on the correlationpatterns of permissions. The system accuracy is 85%for malware applications and goodware applications.
Keywords
Permissions, Android applications, SVD (Singular Value Decomposition), Risk level, Malware, Goodware
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/2325
Journal articles
National Journal of Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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