Vulnerabilities to Online Social Network Identity Deception Detection Research and Recommendations for Mitigation

Max Ismailov, Michail Tsikerdekis and Sherali Zeadally
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Max Ismailov: Computer Science Department, Western Washington University, Bellingham, WA 98225, USA
Michail Tsikerdekis: Computer Science Department, Western Washington University, Bellingham, WA 98225, USA
Sherali Zeadally: College of Communication and Information, University of Kentucky, Lexington, KY 40506, USA

Future Internet, 2020, vol. 12, issue 9, 1-12

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.

Keywords: identity; deception; detection (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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