All Your Fake Detector are Belong to Us: Evaluating Adversarial Robustness of Fake-News Detectors Under Black-Box Settings

With the hyperconnectivity and ubiquity of the Internet, the fake news problem now presents a greater threat than ever before. One promising solution for countering this threat is to leverage deep learning (DL)-based text classification methods for fake-news detection. However, since such methods ha...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Hassan Ali, Muhammad Suleman Khan, Amer Alghadhban, Meshari Alazmi, Ahmad Alzamil, Khaled Al-Utaibi, Junaid Qadir
Format:	Article
Language:	English
Published:	IEEE 2021-01-01
Subjects:	Fake news detection deep neural networks adversarial attacks adversarial robustness
Online Access:	https://ieeexplore.ieee.org/document/9446139/