The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Inferring private information using social network data
Abstract
On-line social networks, such as Facebook, are increasingly utilized by many users. These networks allow people to publish details about themselves and connect to their friends. Some of the information revealed inside these networks is private and it is possible that corporations could use learning algorithms on the released data to predict undisclosed private information. In this paper, we explore how to launch inference attacks using released social networking data to predict undisclosed private information about individuals. We then explore the effectiveness of possible sanitization techniques that can be used to combat such inference attacks under different scenarios.
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Cites
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
SWEENEY, L. (2002) · International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems · doi:10.1142/s0218488502001648 · Cited by 8,571
Cited by
The Quest to Replace Passwords: A Framework for Comparative Evaluation of Web Authentication Schemes
Bonneau, J., Herley, C., Oorschot, P. C. V., & Stajano, F. (2012) · 2012 IEEE Symposium on Security and Privacy · doi:10.1109/sp.2012.44 · Cited by 1,110
What’s in a Name?: Evaluating Statistical Attacks on Personal Knowledge Questions
Bonneau, J., Just, M., & Matthews, G. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-14577-3_10 · Cited by 579
Comprehensive Privacy Analysis on Federated Recommender System Against Attribute Inference Attacks
Zhang, S., Yuan, W., & Yin, H. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2023.3295601 · Cited by 97
Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning
Beigi, G., Mosallanezhad, A., Guo, R., Alvari, H., Nou, A., & Liu, H. (2020) · Proceedings of the 13th International Conference on Web Search and Data Mining · doi:10.1145/3336191.3371832 · Cited by 80
(2017) · doi:10.1145/3038912.3052695 · Cited by 78
Metadata
- Authors
- Lindamood, J., Heatherly, R., Kantarcioglu, M., & Thuraisingham, B.
- Venue
- Proceedings of the 18th international conference on World wide web
- Publisher
- ACM
- Published
- 2009-04-20
- Pages
- 1145-1146
- OpenAlex
- W2135866194
- Cited by
- 221
- References
- 1
- FWCI
- 13.63
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Lindamood, J., Heatherly, R., Kantarcioglu, M., & Thuraisingham, B. (2009). Inferring private information using social network data. Proceedings of the 18th international conference on World wide web. https://doi.org/10.1145/1526709.1526899
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
