Detecting Online Content Deception
| العنوان: | Detecting Online Content Deception |
|---|---|
| المؤلفون: | Michail Tsikerdekis, Sherali Zeadally |
| المصدر: | IT Professional. 22:35-44 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Password, Computer science, media_common.quotation_subject, ComputingMilieux_LEGALASPECTSOFCOMPUTING, 02 engineering and technology, Information integrity, Deception, Computer security, computer.software_genre, Phishing, Computer Science Applications, Metadata, Delivery methods, Hardware and Architecture, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, ComputingMilieux_COMPUTERSANDSOCIETY, Fake news, Content (Freudian dream analysis), computer, Software, media_common |
| الوصف: | The surge of content (such as fake news) in the last few years has made content deception an important area of research. We identify two main types of content deception based on either fake content or misleading content. We present a classification of deception attacks along with their delivery methods. We also discuss defense measures that can detect deception attacks. Finally, we highlight some outstanding challenges in the area of content deception. |
| تدمد: | 1941-045X 1520-9202 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::7c7c69d1733ae246e07e867bb191b37c https://doi.org/10.1109/mitp.2019.2961638 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........7c7c69d1733ae246e07e867bb191b37c |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 1941045X 15209202 |
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