Enhancing malware detection in Android application by incorporating broadcast receivers
, 2021 Rachael Havens +3 more
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MFDroid: A Stacking Ensemble Learning Framework for Android Malware Detection. [PDF]
Sensors (Basel), 2022 Wang X, Zhang L, Zhao K, Ding X, Yu M.
europepmc +1 more source
Android Malware Classification and Optimisation Based on BM25 Score of Android API [PDF]
, 2023 Rahul Yumlembam +3 more
openalex +1 more source
Convolution neural network with batch normalization and inception-residual modules for Android malware classification. [PDF]
Sci Rep, 2022 Liu T, Zhang H, Long H, Shi J, Yao Y.
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Android Malware Detection Systems Review
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2017 With the smartphones entering our lives, the number of smartphones continues to increase day by day. The reason why smartphones are in so demand is that people can easily do what they want. According to IDC's 2016 Q2 report, Android dominated the smartphone market with an 87.6% share [1].
Ömer Kiraz, İbrahim Alper Doğru
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FG-Droid: Grouping based feature size reduction for Android malware detection. [PDF]
PeerJ Comput Sci, 2022 Arslan RS.
europepmc +1 more source
Android malware detection using hybrid ANFIS architecture with low computational cost convolutional layers. [PDF]
PeerJ Comput Sci, 2022 Atacak İ, Kılıç K, Doğru İA.
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Characterization of Android malware based on subgraph isomorphism [PDF]
, 2021 Alain Menelet, Charles‐Edmond Bichot
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Reassessing feature-based Android malware detection in a contemporary context. [PDF]
PLoS OneMuzaffar A +3 more
europepmc +1 more source