Permission-based Analysis of Android Applications Using Categorization and Deep Learning Scheme

作者: Alimardani Hamidreza , Nazeh Mohammed

DOI: 10.1051/MATECCONF/201925505005

关键词:

摘要: As mobile devices grow in popularity, they have become indispensable people's daily lives, keeping us connected to social networks, breaking news, and the entire Internet. While there are multiple competing platforms, Google's Android is currently most popular operating system for devices. This popularity has drawn attention of hackers as well. Thus far, research works analysed permissions individually, which makes analysis complex time consuming. In this work, we propose categorizing based on recommendation perform LSTM data. The used datasets Drebin AndroZoo, complete well-respected among community. experiment results show that achieved 91% true positive rate.

参考文章(26)
Tao Xie, Rahul Pandita, William Enck, Xusheng Xiao, Wei Yang, WHYPER: towards automating risk assessment of mobile applications usenix security symposium. pp. 527- 542 ,(2013)
Borja Sanz, Igor Santos, Xabier Ugarte-Pedrero, Carlos Laorden, Javier Nieves, Pablo G Bringas, None, Instance-based anomaly method for Android malware detection international conference on security and cryptography. pp. 387- 394 ,(2013)
Yousra Aafer, Wenliang Du, Heng Yin, DroidAPIMiner: Mining API-Level Features for Robust Malware Detection in Android Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. pp. 86- 103 ,(2013) , 10.1007/978-3-319-04283-1_6
Wei Xu, Fangfang Zhang, Sencun Zhu, Permlyzer: Analyzing permission usage in Android applications international symposium on software reliability engineering. pp. 400- 410 ,(2013) , 10.1109/ISSRE.2013.6698893
Shuying Liang, Matthew Might, David Van Horn, AnaDroid: Malware Analysis of Android with User-supplied Predicates Electronic Notes in Theoretical Computer Science. ,vol. 311, pp. 3- 14 ,(2015) , 10.1016/J.ENTCS.2015.02.002
David Barrera, H. G üne ş Kayacik, Paul C. van Oorschot, Anil Somayaji, A methodology for empirical analysis of permission-based security models and its application to android Proceedings of the 17th ACM conference on Computer and communications security - CCS '10. pp. 73- 84 ,(2010) , 10.1145/1866307.1866317
Dong-Jie Wu, Ching-Hao Mao, Te-En Wei, Hahn-Ming Lee, Kuo-Ping Wu, DroidMat: Android Malware Detection through Manifest and API Calls Tracing information security. pp. 62- 69 ,(2012) , 10.1109/ASIAJCIS.2012.18
Veelasha Moonsamy, Jia Rong, Shaowu Liu, Mining permission patterns for contrasting clean and malicious android applications Future Generation Computer Systems. ,vol. 36, pp. 122- 132 ,(2014) , 10.1016/J.FUTURE.2013.09.014
Yiming Jing, Gail-Joon Ahn, Ziming Zhao, Hongxin Hu, RiskMon: continuous and automated risk assessment of mobile applications conference on data and application security and privacy. pp. 99- 110 ,(2014) , 10.1145/2557547.2557549
Min Zheng, Mingshen Sun, John C.S. Lui, Droid Analytics: A Signature Based Analytic System to Collect, Extract, Analyze and Associate Android Malware 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications. pp. 163- 171 ,(2013) , 10.1109/TRUSTCOM.2013.25