App. Res. of Comp. Accepted Paper
Vol. 44, 2027 No. 2

Multimodal malware classification based on hierarchical bidirectional cross-attention

Li Li
Wang Yunjing
School of Computer and Artificial Intelligence, Northeast Forestry University, Harbin 150040, China
DOI: 10.19734/j.issn.1001-3695.2026.05.0180

Abstract

To address the problems of insufficient expressive capability of single-modal features and the difficulty of traditional fusion methods in capturing deep cross-modal correlations, we propose a multimodal malicious code classification model named BiCA-MalNet based on a hierarchical bidirectional cross-attention mechanism. The model first constructs three-channel structural feature images, namely W, E, and L, from bytecode files using energy-adaptive wavelet transform, sliding window entropy, and Local Binary Pattern, while simultaneously extracting semantic features from assembly code using GraphCodeBERT. On this basis, we design a channel-wise bidirectional cross-attention mechanism to internally fuse multi-channel image features, and then employ a cross-modal bidirectional cross-attention mechanism to achieve deep interaction and enhancement between image structural features and textual semantic features. On the Microsoft BIG2015 dataset, the model achieves an accuracy of 99.63%, and on the self-constructed PEDataset, it achieves 95.18%. Experimental results demonstrate that the proposed hierarchical bidirectional cross-attention fusion strategy can effectively improve the classification performance of complex malicious code.

Foundation Support

黑龙江省重点研发计划项目(黑龙江省科技厅)(2022ZX01A30)
黑龙江省"揭榜挂帅"科技攻关项目(黑龙江省科技厅)(2023ZXJ02C03)
2024年度黑龙江省高等教育教学改革研究重点项目(黑龙江省教育厅)(SJGZB2024069)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.05.0180
Publish at: Application Research of Computers Accepted Paper, Vol. 44, 2027 No. 2

Publish History

[2026-10-23] Accepted Paper

Cite This Article

李莉, 王云静. 基于分层双向交叉注意力的多模态恶意代码分类 [J]. 计算机应用研究, 2027, 44 (2). (2026-10-24). https://doi.org/10.19734/j.issn.1001-3695.2026.05.0180. (Li Li, Wang Yunjing. Multimodal malware classification based on hierarchical bidirectional cross-attention [J]. Application Research of Computers, 2027, 44 (2). (2026-10-24). https://doi.org/10.19734/j.issn.1001-3695.2026.05.0180. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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