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January 1, 2026International Journal of Security and Networks

MWO-ACDR-LSTM: Android Malware Detection Using Attentional Deep Learning Model

Pallavi Madhukarrao Shimpi Nitin Pise

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Key Points

The aim is to develop an attentional deep learning model for detecting malware on Android devices.
Developed a model named MWO-ACDR-LSTM utilizing deep learning techniques.
Implemented algorithms to analyze app behavior and identify malicious patterns.
Evaluated model performance using various metrics for accuracy and reliability.
Showed improved detection rates for Android malware compared to existing methods.
Achieved high accuracy and low false positive rates in testing scenarios.

Implication

Demonstrates effective malware detection in Android devices, suggesting enhanced protection against cyber threats.

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Cite This Study

Shimpi et al. (2026) studied this question.

synapsesocial.com/papers/69c7725e8bbfbc51511e2cde https://doi.org/10.1504/ijsn.2026.10077286

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