A multi-tiered feature selection model for android malware detection based on Feature discrimination and Information Gain

Author:

Bhat Parnika,Dutta Kamlesh

Funder

Ministry of Human Resource Development

Publisher

Elsevier BV

Subject

General Computer Science

Reference61 articles.

1. A. Developers, Permissions on android, Permissions, Available: URL:https://developer.android.com/guide/topics/permissions/overview (2021).

2. Anael Beaugnon, A.H., 2018. Pierre Collet, Detection performance metrics, Detection Rate, Available: URL:https://anssi-fr.github.io/SecuML/miscellaneous.detection_perf.html#::text=The%20confusion%20matrix%20allows%20to,PTP%2BFN.

3. AndroPyTool, Andropytool, GitHub, Available:URL:https://github.com/alexMyG/AndroPyTool (2019).

4. Arp, D., Spreitzenbarth, M., Hübner, M., Gascon, H., Rieck, K., 2014. Drebin: Effective and explainable detection of android malware in your pocket, Symposium on Network and Distributed System Security (NDSS) (02 2014). doi:10.14722/ndss.2014.23247.

5. Artyom Skrobov, S.M., 2019. Advanced sms phishing attacks against modern android-based smartphones, Check Point Software Technologies LTD, Available: URL:https://research.checkpoint.com/advanced-sms-phishing-attacks-against-modern-android-based-smartphones/.

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