Author

P. Shimpi

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Open access Jul 2026

Android Malware Detection Using an Optimized and Explainable Attentional Convolutional LSTM Model

The proposed optimized and interpretable attentional CNN–LSTM framework for Android malware detection utilizes convolutional layer to extract spatial features, Long Short-Term Memory networks to capture patterns in sequential behavior and attention mechanism to highlight distinctive sequences of API calls.

P. Shimpi, N. Pise · Journal of Intelligent Decis... · 0 citations