Online Social Network
Keywords:
Social Network, Privacy Preservation, multiparty access control, Photo SharingAbstract
Online Social Networks (OSNs) such as Facebook, Google, and Twitter are inherently designed to enable people to share personal and public information and make social connections with friends, coworkers, colleagues, family, and even with strangers. A typical OSN provides each user with a virtual space containing profile information, a list of the user’s friends, and web pages, such as wall in Facebook, where users and friends can post content and leave messages. In addition, users can not only upload content into their own or others’ spaces but also tag other users who appear in the content. Although OSNs currently provide simple access control mechanisms allowing users to govern access to information contained in their own spaces, users, unfortunately, have no control over data residing outside their spaces. To overcome the problem based on Online Social Networks, a systematic solution to facilitate multiparty access control (MPAC) of shared data in OSNs is introduced. The user can share their data or images to their friends. When the user is tried to share other user’s data, the request will be send to the owner of the data. After receiving the request, the owner of the data has rights to accept or reject the request. The User can only share others data after getting the approval from the data owner, otherwise the user cannot share that data to others.
References
- Altman. Privacy regulation: Culturally universal or culturally specific? Journal of Social Issues, 33(3):66–84, 1977
- 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.
- 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
- 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.
- 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.
- K.-B. Duan and S. S. Keerthi. Which is the best multiclass svm method? an empirical study. In Proceedings of the 6th international conference on Multiple Classifier Systems, MCS’05, pages 278–285, Berlin, Heidelberg, 2005. Springer-Verlag.
- L. Palen. Unpacking privacy for a networked world. pages 129– 136. Press, 2003.
- M. E. Newman. The structure and function of complex networks. SIAM review, 45(2):167–256, 2003.
- N. Mavridis, W. Kazmi, and P. Toulis. Friends with faces: How social networks can enhance face recognition and vice versa. In Computational Social Network Analysis, Computer Communications and Networks, pages 453–482. Springer London, 2010.
- L. Kissner and D. X. Song. Privacy-preserving set operations. In V. Shoup, editor, CRYPTO, volume 3621 of Lecture Notes in Computer Science, pages 241–257. Springer, 2005
Downloads
Published
Issue
Section
License
Copyright (c) IJSRST
This work is licensed under a Creative Commons Attribution 4.0 International License.