Is Multi-Modal Necessarily Better? Robustness Evaluation of Multi-Modal Fake News Detection
| Autor: | Jinyin Chen, Chengyu Jia, Haibin Zheng, Ruoxi Chen, Chenbo Fu |
|---|---|
| Rok vydání: | 2023 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Computer Science - Computers and Society Artificial Intelligence (cs.AI) Computer Science - Artificial Intelligence Computer Networks and Communications Control and Systems Engineering Computers and Society (cs.CY) Computer Science - Social and Information Networks Computer Science Applications |
| Zdroj: | IEEE Transactions on Network Science and Engineering. :1-15 |
| ISSN: | 2334-329X |
| Popis: | The proliferation of fake news and its serious negative social influence push fake news detection methods to become necessary tools for web managers. Meanwhile, the multi-media nature of social media makes multi-modal fake news detection popular for its ability to capture more modal features than uni-modal detection methods. However, current literature on multi-modal detection is more likely to pursue the detection accuracy but ignore the robustness of the detector. To address this problem, we propose a comprehensive robustness evaluation of multi-modal fake news detectors. In this work, we simulate the attack methods of malicious users and developers, i.e., posting fake news and injecting backdoors. Specifically, we evaluate multi-modal detectors with five adversarial and two backdoor attack methods. Experiment results imply that: (1) The detection performance of the state-of-the-art detectors degrades significantly under adversarial attacks, even worse than general detectors; (2) Most multi-modal detectors are more vulnerable when subjected to attacks on visual modality than textual modality; (3) Popular events' images will cause significant degradation to the detectors when they are subjected to backdoor attacks; (4) The performance of these detectors under multi-modal attacks is worse than under uni-modal attacks; (5) Defensive methods will improve the robustness of the multi-modal detectors. |
| Databáze: | OpenAIRE |
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