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

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posted on 2021-05-28, 16:48 authored by Hassan AliHassan Ali, Muhammad Suleman Khan, Amer AlGhadhban, Meshari Alazmi, Ahmad Alzamil, Khaled AlUtaibi, Junaid QadirJunaid Qadir
Analyzing fake-news detectors under adversarial threat using the Text-Attack Library for a number of model hyper-parameters and attack settings.

Funding

Deputy for Research and Innovation, Ministry of Education, Kingdom of Saudi Arabia - (IFP-2004)

History

Email Address of Submitting Author

hali.msee17seecs@seecs.edu.pk

ORCID of Submitting Author

0000-0002-1701-0390

Submitting Author's Institution

Information Technology University, Lahore

Submitting Author's Country

Pakistan

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Keywords

Fake news detectionNatural language processingAdversarial AttacksAdversarial Robustness

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CC BY-NC-SA 4.0

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