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General android malware behaviour taxonomy
Nowadays, with rapid advancement of technology, a smartphone has significant risks as they contain sensitive information and can lead to serious security risks if it falls into unauthorised persons.
Husna Zayadi
core
The purpose of this report is to provide an insight to the findings gathered during the 1 year Final Year Project (FYP) period researching on Android Malware Analysis.
Chia, Liang Chuan.
core
The datasets used in this study: CIC-AndMal2017, CIC-MalDroid2020, and Drebin, provide curated and structured information for Android malware analysis.
Haque, Md Sadman
core +1 more source
On the evaluation of android malware detectors against code-obfuscation techniques. [PDF]
Nawaz U, Aleem M, Lin JC.
europepmc +1 more source
Androfim: few-shot android malware family detection based on image representation
Android malware is the major cyber threat to the popular Android platform which may influence millions of end users. To battle against the Android malware, a large number of machine learning methods either based on 1) traditional feature extraction using
Fan Zhou +4 more
doaj +1 more source
Android malware detection method based on highly distinguishable static features and DenseNet. [PDF]
Yang J, Zhang Z, Zhang H, Fan J.
europepmc +1 more source
An Android Malware Detection Approach to Enhance Node Feature Differences in a Function Call Graph Based on GCNs. [PDF]
Wu H, Luktarhan N, Tian G, Song Y.
europepmc +1 more source
Evaluation and classification of obfuscated Android malware through deep learning using ensemble voting mechanism. [PDF]
Aurangzeb S, Aleem M.
europepmc +1 more source
Lightweight On-Device Detection of Android Malware Based on the Koodous Platform and Machine Learning. [PDF]
Krzysztoń M, Bok B, Lew M, Sikora A.
europepmc +1 more source
An Analysis of Android Malware Classification Services. [PDF]
Rashed M, Suarez-Tangil G.
europepmc +1 more source

