Detecting Online Content Deception

Michail Tsikerdekis, Sherali Zeadally

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Article number9049293
Pages (from-to)35-44
Number of pages10
JournalIT Professional
Volume22
Issue number2
DOIs
StatePublished - Mar 1 2020

Bibliographical note

Publisher Copyright:
© 1999-2012 IEEE.

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Detecting Online Content Deception'. Together they form a unique fingerprint.

Cite this