Vulnerabilities to online social network identity deception detection research and recommendations for mitigation

Max Ismailov, Michail Tsikerdekis, Sherali Zeadally

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations

Abstract

Identity deception in online social networks is a pervasive problem. Ongoing research is developing methods for identity deception detection. However, the real-world efficacy of these methods is currently unknown because they have been evaluated largely through laboratory experiments. We present a review of representative state-of-the-art results on identity deception detection. Based on this analysis, we identify common methodological weaknesses for these approaches, and we propose recommendations that can increase their effectiveness for when they are applied in real-world environments.

Original languageEnglish
Article number148
Pages (from-to)1-12
Number of pages12
JournalFuture Internet
Volume12
Issue number9
DOIs
StatePublished - Sep 2020

Bibliographical note

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Deception
  • Detection
  • Identity

ASJC Scopus subject areas

  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Vulnerabilities to online social network identity deception detection research and recommendations for mitigation'. Together they form a unique fingerprint.

Cite this