Spotting Fake Profiles in Social Networks via Keystroke Dynamics Article Swipe
Alvin Kuruvilla
,
Rojanaye Daley
,
Rajesh Kumar
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2311.06903
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2311.06903
Spotting and removing fake profiles could curb the menace of fake news in society. This paper, thus, investigates fake profile detection in social networks via users' typing patterns. We created a novel dataset of 468 posts from 26 users on three social networks: Facebook, Instagram, and X (previously Twitter) over six sessions. Then, we extract a series of features from keystroke timings and use them to predict whether two posts originated from the same users using three prominent statistical methods and their score-level fusion. The models' performance is evaluated under same, cross, and combined-cross-platform scenarios. We report the performance using k-rank accuracy for k varying from 1 to 5. The best-performing model obtained accuracies between 91.6-100% on Facebook (Fusion), 70.8-87.5% on Instagram (Fusion), and 75-87.5% on X (Fusion) for k from 1 to 5. Under a cross-platform scenario, the fusion model achieved mean accuracies of 79.1-91.6%, 87.5-91.6%, and 83.3-87.5% when trained on Facebook, Instagram, and Twitter posts, respectively. In combined cross-platform, which involved mixing two platforms' data for model training while testing happened on the third platform's data, the best model achieved accuracy ranges of 75-95.8% across different scenarios. The results highlight the potential of the presented method in uncovering fake profiles across social network platforms.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2311.06903
- https://arxiv.org/pdf/2311.06903
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388685076
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388685076Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2311.06903Digital Object Identifier
- Title
-
Spotting Fake Profiles in Social Networks via Keystroke DynamicsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-11-12Full publication date if available
- Authors
-
Alvin Kuruvilla, Rojanaye Daley, Rajesh KumarList of authors in order
- Landing page
-
https://arxiv.org/abs/2311.06903Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2311.06903Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2311.06903Direct OA link when available
- Concepts
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Spotting, Computer science, Keystroke dynamics, Social media, Keystroke logging, Social network (sociolinguistics), Dialog box, Artificial intelligence, Sensor fusion, Machine learning, World Wide Web, Computer security, S/KEY, PasswordTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.platforms' | 165 |
| abstract_inverted_index.platforms. | 205 |
| abstract_inverted_index.scenarios. | 94, 188 |
| abstract_inverted_index.uncovering | 199 |
| abstract_inverted_index.(previously | 47 |
| abstract_inverted_index.79.1-91.6%, | 145 |
| abstract_inverted_index.87.5-91.6%, | 146 |
| abstract_inverted_index.performance | 86, 98 |
| abstract_inverted_index.score-level | 82 |
| abstract_inverted_index.statistical | 78 |
| abstract_inverted_index.investigates | 17 |
| abstract_inverted_index.respectively. | 157 |
| abstract_inverted_index.cross-platform | 136 |
| abstract_inverted_index.best-performing | 110 |
| abstract_inverted_index.cross-platform, | 160 |
| abstract_inverted_index.combined-cross-platform | 93 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile |