Protecting by attacking: A personal information protecting method with cross-modal adversarial examples
Zhao, Mengnan2; Wang, Bo1; Guo, Weikuo1; Wang, Wei3
刊名NEUROCOMPUTING
2023-09-28
卷号551页码:11
关键词Security Cross-modal Image captioning Adversarial attacks
ISSN号0925-2312
DOI10.1016/j.neucom.2023.126481
通讯作者Wang, Bo(bowang@dlut.edu)
英文摘要Recent years' development of AI technology brings more convenience to our life while at the same time increasing the risk of personal information leakage. In this work, we try to protect personal information contained in the images by generating adversarial examples to fool the image captioning models. The generated adversarial examples are user-oriented which means the users can manipulate or hide sensitive information on the text output as they wish. By doing so, our personal information can be well protected from image captioning models. To fulfill the task, we adopt five kinds of adversarial attack. Experimental results show our method can successfully protect user security. The Pytorch & REG; implementations can be downloaded from an open-source GitHub project (https://github.com/Dlut-lab-zmn/ImageCaptioning-Attack/). & COPY; 2023 Elsevier B.V. All rights reserved.
WOS研究方向Computer Science
语种英语
出版者ELSEVIER
WOS记录号WOS:001033827500001
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/53789]  
专题多模态人工智能系统全国重点实验室
通讯作者Wang, Bo
作者单位1.Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116081, Peoples R China
2.Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116081, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100089, Peoples R China
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GB/T 7714
Zhao, Mengnan,Wang, Bo,Guo, Weikuo,et al. Protecting by attacking: A personal information protecting method with cross-modal adversarial examples[J]. NEUROCOMPUTING,2023,551:11.
APA Zhao, Mengnan,Wang, Bo,Guo, Weikuo,&Wang, Wei.(2023).Protecting by attacking: A personal information protecting method with cross-modal adversarial examples.NEUROCOMPUTING,551,11.
MLA Zhao, Mengnan,et al."Protecting by attacking: A personal information protecting method with cross-modal adversarial examples".NEUROCOMPUTING 551(2023):11.
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