App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 9

Adversarial robustness enhanced multimodal rumor detection method

Li Jing1,2,3
Chen Xinyu1,2,3
Tang Rui1,2,3
Wang Wenxian1,2,3
Wang Haizhou1,2,3
1. School of Cyber Science and Engineering, Sichuan University, Chengdu 610065, China
2. Key Laboratory of Data Protection and Intelligent Management, Ministry of Education, Chengdu 610065, China
3. China Cyber Science Research Institute, Sichuan University, Chengdu 610065, China
DOI: 10.19734/j.issn.1001-3695.2026.01.0005

Abstract

To address the limitations of existing rumor detection datasets being unimodal and the weak robustness of rumor detection models against multimodal attacks, this paper constructed a large-scale multimodal rumor dataset, MuRumor. This dataset contains 19, 733 posts, 658, 557 comments, and 12, 365 users, covering text, image, comment, user, and social context features. Subsequently, an Adversarial Robustness-enhanced Multimodal Rumor Detection (AR-MRD) model was proposed. The model introduced text style weakening, comment filtering, and image adversarial training mechanisms, combined with a comment-assisted cross-modal consistency mechanism, achieving efficient fusion of multimodal features and significantly improving the model's resistance to cross-modal adversarial attacks. Experimental results show that AR-MRD achieves an accuracy of 92.4%, surpassing existing detection methods, and maintains the lowest attack success rate under adversarial conditions, indicating its effectiveness in defending against tampering attacks on text, image, and comment modalities.

Foundation Support

国家重点研发计划(2022YFC3303101)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.01.0005
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 9

Publish History

[2026-05-29] Accepted Paper

Cite This Article

李婧, 陈欣雨, 唐瑞, 等. 基于对抗鲁棒增强的多模态谣言检测方法 [J]. 计算机应用研究, 2026, 43 (9). (2026-06-02). https://doi.org/10.19734/j.issn.1001-3695.2026.01.0005. (Li Jing, Chen Xinyu, Tang Rui, et al. Adversarial robustness enhanced multimodal rumor detection method [J]. Application Research of Computers, 2026, 43 (9). (2026-06-02). https://doi.org/10.19734/j.issn.1001-3695.2026.01.0005. )

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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