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Journal : ILKOMNIKA: Journal of Computer Science and Applied Informatics

Generalization Analysis of a Long Short-Term Memory Model for Cross-Domain Malware Detection Prasetyo, Stefanus Eko; Haeruddin, Haeruddin; Jason, Jason
ILKOMNIKA Vol 8 No 1 (2026): Volume 8, Number 1, April 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v8i1.856

Abstract

The increasing diversity of malware targeting heterogeneous computing environments poses significant challenges to conventional detection approaches that rely on domain-specific assumptions. In particular, detection models optimized for a single dataset often exhibit limited robustness when applied to data with different structural and behavioral characteristics. This study analyzes the generalization capability of a Long Short-Term Memory (LSTM) model for behavior-based malware detection across multiple domains. A fixed two-layer LSTM architecture is evaluated using one primary dataset, CIC-MalMem-2022, and four additional datasets representing Android applications, Internet of Things network traffic, botnet behavior, and static Windows Portable Executable analysis. Although each dataset undergoes a dataset-specific preprocessing pipeline, all experiments employ an identical model architecture and hyperparameter configuration to ensure consistent and comparable evaluation. Model performance is assessed using standard classification metrics, supported by single train–test evaluation and five-fold cross-validation to examine performance stability and robustness. The experimental results demonstrate that the LSTM model maintains consistently high detection performance across datasets with diverse characteristics, including both sequential and non-sequential data representations. These findings indicate that the model effectively captures fundamental malware behavior patterns that generalize beyond a single domain, highlighting its potential applicability in heterogeneous cybersecurity environments where cross-domain robustness is required. At the same time, the evaluation is conducted under controlled experimental conditions and does not explicitly address adversarial adaptation or fully dynamic runtime deployment, which should be considered when interpreting the results for practical operational use.
Co-Authors ., Arron ., Kennedi Abner Onesimus Sijabat Agung Wijaya Ardyansyah Wijaya Ari Wahyuni Kaharuddin Ari Wibowo Ariesryo, Kelvin Aripradono, Heru Wijayanto Avista Mindy Basri, Germen Benny Benny Burhan, Rifa’atul M. Candra, Boby candra, joni eka Chandra Wijaya, Kevin Christina, Lidya Conny Agustin Dede Hilman Rasyid Dendi, Dendi Deven Lee Dini Sari Melati Dominggo Givarel Elia Elia Elvin Elvin Elvin Tan Elvin Tan Elvis Elvis, Elvis Fadil Mahendra Favian, Felix Febby Anggellya Felix Felix Yeovandi Fiona Livianti Frandika Antonius Saputra Frans Hadinata Gautama Wijaya Gusti Irawan Haeruddin Haeruddin Haeruddin Haeruddin, . Hansen, Irvan Haryono Haryono Hasanah, Nafisatul Jackson Jackson Jason, Jason Jefri Jefri Jemmy Jemmy Jemmy, Jemmy Jhon Lim Jimmy Cung Johan Johan Jonathan Felix Andrianto Kaharuddin, Ari Wahyuni Kelvin Ariesryo Kevin, Kevin Kwan, Allan Lau, Wilsen Melisa Melisa Mindy, Avista Mitha Veronica Muhammad Jufri Muhammad Yaasin Nafisatul Hasanah Nafisatul Hasanah Nimatul Mamuriyah Noviardi, Refli Nurul Hassanah Princessa Princessa Puteri, Vier Adinda Putri Syahfira Raja Muhammad Isnu Prayoga Ricardo Ricky Chandra Lee Robby Robby Ruby Shafira Rushadi Sabariman Sabariman Sabariman Sabariman Sama, Hendi Sijabat, Abner Onesimus Sopiyan, Sopiyan Stefanie Steny Steny Steven Lie Sugianto Sugianto Sun Pho Syaeful Anas Aklani, Syaeful Syahfira, Putri Tony Jack Tan Ding Try Windranata Try Windranata Vincent Theo Weni Vivianti Wijaya, Gautama Yuki Estrada Yulfan Salimin Yulianto, Andik