Kafalı, Özgur and Günay, Akin and Yolum, Pinar (2013) Protoss: A run time tool for detecting privacy violations in online social networks: Short Paper. In: 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. IEEE, pp. 429-433. ISBN 978-1-4673-2497-7. (doi:10.1109/ASONAM.2012.76) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:65887)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1109/ASONAM.2012.76 |
Abstract
As online social networks are becoming part of both social and work life, preserving privacy of their users is becoming tremendously difficult. While these social networks are promising privacy through privacy agreements, everyday new privacy leakages are emerging. Ideally, online social networks should be able to manage and maintain their agreements through well-founded methods. However, the dynamic nature of the online social networks is making it difficult to keep private information contained. We have developed PROTOSS, a run time tool for detecting privacy leakages in online social networks. PROTOSS captures relations among users, their privacy agreements with an online social network operator, and domain-based inference rules. It then uses model checking to detect if an online social network will leak private information.
Item Type: | Book section |
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DOI/Identification number: | 10.1109/ASONAM.2012.76 |
Subjects: | Q Science > Q Science (General) > Q335 Artificial intelligence |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Ozgur Kafali |
Date Deposited: | 04 Feb 2018 19:30 UTC |
Last Modified: | 05 Nov 2024 11:04 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/65887 (The current URI for this page, for reference purposes) |
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