Aug 7, 2022 · This study proposes DeepCatra, a multi-view learning approach for Android malware detection, whose model consists of a bidirectional LSTM (BiLSTM) and a graph ...
Jan 30, 2022 · In this paper, we propose DeepCatra, a multi-view learning approach for Android malware detection, whose model consists of a bidirectional LSTM (BiLSTM) and a ...
Experimental results on over 18,000 real‐world apps and prevalent malware show that DeepCatra achieves considerable improvement, for example, 2.7%–14.6% on the ...
DeepCatra, a multi-view learning approach for Android malware detection, whose model consists of a bidirectional LSTM (BiLSTM) and a graph neural network ...
DeepCatra [50] is designed to detect the malware behaviors of Android APPs. DeepCatra consists of a bidirectional LSTM (BiLSTM) and a GNN, which is trained on ...
Aug 7, 2022 · As Android malware grows and evolves, deep learning has been introduced into malware detection, resulting in great effectiveness.
Jan 30, 2022 · As Android malware is growing and evolving, deep learning has been introduced into malware detection, resulting in great effectiveness.
DeepCatra: Learning Flow- and Graph-based Behaviors for Android Malware Detection. This is the code and data repository of DeepCatra. Directory structure.
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Mar 1, 2024 · This paper proposes a novel Android malware detection method that integrates multiple features of Android applications.
In this paper, we propose a novel approach to Android malware analysis and categorization that leverages the power of BERT (Bidirectional Encoder ...