TRUST BASED PROFILE COORDINATING SECURE SOCIAL SYSTEMS
Authors/Creators
Description
The statistics of photo sharing on social networks proposes a three realms
model: a social realm, in which identities are entities, and friendship is a relation;
second, a visual sensory realm, of which faces are entities, and co-occurrence in
images a relation; and third, a physical realm, in which bodies belong, with physical
proximity being a relation. Information sharing is an attractive feature which
popularizes Online Social Networks (OSNs). To prevent possible privacy leakage of
photos, we design a mechanism to enable each individual in a photo be aware of the
posting activity and participate in the decision making on the posting and tagging.
Unfortunately, it may leak users’ privacy if they are allowed to post, comment, and
tag a photo freely. If a request is sent to another person it will show the matches and
mismatches. Then for user tagging or adding to a group it will not automatically tag
it will ask for permission from the user. Each user is able to define his/her privacy
policy and exposure policy. Only when a photo is processed with owner’s privacy
policy and co-owner’s exposure policy could it be posted. However, the co-owners
of a co-photo cannot be determined automatically, instead, potential co-owners
could only be identified by using the tagging features on the current OSNs.
Files
TRUST BASED PROFILE COORDINATING SECURE SOCIAL SYSTEMS.pdf
Additional details
References
- [1] I. Altman. Privacy regulation: Culturally universal or culturally specific? Journal of Social Issues, 33(3):66–84, 1977
- [2] A. Besmer and H. Richter Lipford. Moving beyond untagging: photo privacy in a tagged world. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '10, pages 1563–1572, New York, NY, USA, 2010. ACM.
- [3] S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein. Distributed optimization and statistical learning via the alternating direction method of multipliers. Found. Trends Mach. Learn., 3(1):1–122, Jan. 2011.
- [4] B. Carminati, E. Ferrari, and A. Perego. Rule-based access control for social networks. In R. Meersman, Z. Tari, and P. Herrero, editors, On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops, volume 4278 of Lecture Notes in Computer Science, pages 1734–1744. Springer Berlin Heidelberg, 2006.
- [5] J. Y. Choi, W. De Neve, K. Plataniotis, and Y.-M. Ro. Collaborative face recognition for improved face annotation in personal photo collections shared on online social networks. Multimedia, IEEE Transactions on, 13(1):14–28, 2011.
- [6] K. Choi, H. Byun, and K.-A. Toh. A collaborative face recognition framework on a social network platform. In Automatic Face Gesture Recognition, 2008. FG '08. 8th IEEE International Conference on, pages 1–6, 2008.
- [7] Z. Stone, T. Zickler, and T. Darrell. Toward large-scale face recognition using social network context. Proceedings of the IEEE, 98(8):1408–1415.
- [8] Z. Stone, T. Zickler, and T. Darrell. Autotagging facebook: Social network context improves photo annotation. In Computer Vision and Pattern Recognition Workshops, 2008. CVPRW'08. IEEE Computer Society Conference on, pages 1–8. IEEE, 2008.