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

Autor:	Max Ismailov, Michail Tsikerdekis, Sherali Zeadally
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	identity deception detection Information technology T58.5-58.64
Zdroj:	Future Internet, Vol 12, Iss 9, p 148 (2020)
Druh dokumentu:	article
ISSN:	1999-5903
DOI:	10.3390/fi12090148
Popis:	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.
Databáze:	Directory of Open Access Journals
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