دورية أكاديمية
A Survey of Detection and Mitigation for Fake Images on Social Media Platforms
| العنوان: | A Survey of Detection and Mitigation for Fake Images on Social Media Platforms |
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| المؤلفون: | Dilip Kumar Sharma, Bhuvanesh Singh, Saurabh Agarwal, Lalit Garg, Cheonshik Kim, Ki-Hyun Jung |
| المصدر: | Applied Sciences, Vol 13, Iss 19, p 10980 (2023) |
| بيانات النشر: | MDPI AG, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| مصطلحات موضوعية: | deep learning, digital image forensic, fake images, generated adversarial networks, multi-modal, image forgery detection, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| الوصف: | Recently, the spread of fake images on social media platforms has become a significant concern for individuals, organizations, and governments. These images are often created using sophisticated techniques to spread misinformation, influence public opinion, and threaten national security. This paper begins by defining fake images and their potential impact on society, including the spread of misinformation and the erosion of trust in digital media. This paper also examines the different types of fake images and their challenges for detection. We then review the recent approaches proposed for detecting fake images, including digital forensics, machine learning, and deep learning. These approaches are evaluated in terms of their strengths and limitations, highlighting the need for further research. This paper also highlights the need for multimodal approaches that combine multiple sources of information, such as text, images, and videos. Furthermore, we present an overview of existing datasets, evaluation metrics, and benchmarking tools for fake image detection. This paper concludes by discussing future directions for fake image detection research, such as developing more robust and explainable methods, cross-modal fake detection, and the integration of social context. It also emphasizes the need for interdisciplinary research that combines computer science, digital forensics, and cognitive psychology experts to tackle the complex problem of fake images. This survey paper will be a valuable resource for researchers and practitioners working on fake image detection on social media platforms. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 13191098 2076-3417 |
| Relation: | https://www.mdpi.com/2076-3417/13/19/10980; https://doaj.org/toc/2076-3417 |
| DOI: | 10.3390/app131910980 |
| URL الوصول: | https://doaj.org/article/d6a9d139cc0b4407aa5bfe63433e4dd1 |
| رقم الأكسشن: | edsdoj.6a9d139cc0b4407aa5bfe63433e4dd1 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 13191098 20763417 |
|---|---|
| DOI: | 10.3390/app131910980 |