Adaptive Frequency Domain and Transformer-Based Fusion Network for Advanced Android Malware Defense

Author(s)	Ms. Mounika K, Ms. Indhu R, Ms. Priyambika S, Mr. Pavan Kumar S, Mr. T Hema Charan Royal
Country	India
Abstract	Android malware is malicious software that targets Android devices to steal data, display unwanted advertisements, or gain unauthorized control. Traditional malware detection methods such as signature-based and static analysis struggle to detect new and obfuscated malware variants. This research proposes an advanced detection framework that combines adaptive frequency domain analysis, recursive feature fusion, and transformer-based attention mechanisms. The proposed system improves detection accuracy and enhances security against evolving Android malware threats.
Keywords	Android malware, spatial feature obfuscation techniques, transformer-based attention mechanisms, adversarial robustness, dynamic analysis.
Field	Engineering
Published In	Volume 7, Issue 3, March 2026
Published On	2026-03-20
DOI	https://doi.org/10.70528/IJLRP.v7.i3.2009
Short DOI	https://doi.org/hbtbqx

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