Approaches for Fake Content Detection: Strengths and Weaknesses to Adversarial Attacks
| العنوان: | Approaches for Fake Content Detection: Strengths and Weaknesses to Adversarial Attacks |
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| المؤلفون: | Sherali Zeadally, Michail Tsikerdekis, Matthew Carter |
| المصدر: | IEEE Internet Computing. 25:73-83 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Computer Networks and Communications, Network security, business.industry, Computer science, Deep learning, Feature extraction, 020206 networking & telecommunications, 02 engineering and technology, Computer security, computer.software_genre, Adversarial system, 0202 electrical engineering, electronic engineering, information engineering, The Internet, Artificial intelligence, Fake news, business, Content (Freudian dream analysis), computer, Strengths and weaknesses |
| الوصف: | In the last few years, we have witnessed an explosive growth of fake content on the Internet which has significantly affected the veracity of information on many social platforms. Much of this disruption has been caused by the proliferation of advanced machine and deep learning methods. In turn, social platforms have been using the same technological methods in order to detect fake content. However, there is understanding of the strengths and weaknesses of these detection methods. In this article, we describe examples of machine and deep learning approaches that can be used to detect different types of fake content. We also discuss the characteristics and the potential for adversarial attacks on these methods that could reduce the accuracy of fake content detection. Finally, we identify and discuss some future research challenges in this area. |
| تدمد: | 1941-0131 1089-7801 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::528c111e80626f9d515f7e12e813ecbd https://doi.org/10.1109/mic.2020.3032323 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........528c111e80626f9d515f7e12e813ecbd |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 19410131 10897801 |
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