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Vulnerabilities to Online Social Network Identity Deception Detection Research and Recommendations for Mitigation
| Content Provider | MDPI |
|---|---|
| Author | Ismailov, Max Tsikerdekis, Michail Zeadally, Sherali |
| Copyright Year | 2020 |
| Description | 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. |
| Starting Page | 148 |
| e-ISSN | 19995903 |
| DOI | 10.3390/fi12090148 |
| Journal | Future Internet |
| Issue Number | 9 |
| Volume Number | 12 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2020-08-31 |
| Access Restriction | Open |
| Subject Keyword | Future Internet Information and Library Science Identity Deception Detection |
| Content Type | Text |
| Resource Type | Article |
