Android malware dynamic evasions

Citation Author(s):
Hayyan
Hasan
MDSE Research Group, Department of Software Engineering, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
Hasan
Deeb
Department of Software Engineering and Information Systems, Faculty of Informatics Engineering, Albaath university, Homs, Syria
Behrouz
Tork Ladani
MDSE Research Group, Department of Software Engineering, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
Bahman
Zamani
MDSE Research Group, Department of Software Engineering, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
Submitted by:
hayyan hasan
Last updated:
Wed, 06/16/2021 - 09:41
DOI:
10.21227/njbg-3c03
License:
0
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Abstract 

This dataset is a hand noted dataset that consists of two categories, evasion and normal methods. By evasion methods we mean the methods that are used by Android malware to hide their malicious payload, and hinder the dynamic analysis. Normal methods are any other methods that cannot be used as evasion techniques. Also, the evasion methods are categorized into six categories: File access, Integrity check, Location, SMS, Time, Anti-emulation. This dataset can be used by any ML or DL approaches to predict new evasion techniques that can be used by malware to hinder the dynamic analysis.

Instructions: 

This dataset can be used by ML or DL approaches to predict new evasion techniques that are used by Android malware.

In order to do so, the Android API methods are needed

Comments

Hey

Submitted by James Lin on Fri, 10/22/2021 - 23:12