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

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Publication Details

Journal
International Journal of Security and Networks
Published
2026-01-01
DOI
https://doi.org/10.1504/ijsn.2026.10077286
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Nitin Pise, Pallavi Madhukarrao Shimpi
International Journal of Security and Networks
Advanced Malware Detection Techniques
article

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

Nitin Pise, Pallavi Madhukarrao Shimpi
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Security and NetworksVol. 1(1)
Openalex Percentile: Top 6%
Advanced Malware Detection Techniques
DOISourceOpenAlex
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MWO-ACDR-LSTM: Android Malware Detection Using Attentional Deep Learning Model — Nitin Pise, Pallavi Madhukarrao Shimpi · International Journal of Security and Networks (2026) | TGRS Research Map | TGRS