IJRCS – Volume 1 Issue 3 Paper 6

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ACCESS CONTROL THROUGH USER DECISION IN ONLINE SOCIAL NETWORK USING MODEL ACCESS CONTROL

Author’s Name : Simikutty Antony | R Sujitha

Volume 01 Issue 03  Year 2014  ISSN No:  2349-3828  Page no:  24-28

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Abstract:

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 WebPages, 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.

Keywords:

Social Network, Photo Privacy, Secure Multiparty Communication,Support Vector Machine, Collaborative Learning

References:

  1. Altman. Privacy regulation: Culturally universal or culturally specific? Journal of Social Issues, 33(3):66–84, 1977.
  2. Besmer and H. Richter Lipford. Moving beyond untagging: photo privacy in a tagged world. In Proceedings of the SIGCH IConference on Human Factors in Computing Systems, CHI ’10, pages1563–1572, New York, NY, USA, 2010. ACM
  3. S. Boyd, N. Parikh, E. Chu, B. Plato, 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 controlfor social networks. In R. Meersman, Z. Tari, and P. Herrero,editors, On the Move to Meaningful Internet Systems 2006: OTM2006 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. Collaborativeface recognition for improved face annotation in personal photocollections shared on online social networks. Multimedia, IEEETransactions on, 13(1):14–28, 2011.
  6. K. Choi, H. Byun, and K.-A. Toh. A collaborative face recognitionframework on a social network platform. In Automatic Face Gesture Recognition, 2008. FG ’08. 8th IEEE International Conference on,pages 1–6, 2008.
  7. K.-B. Duan and S. S. Keerthi. Which is the best multi class 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.
  8. P. A. Forero, A. Cano, and G. B. Giannakis. Consensus- based distributed support vector machines. J. Mach. Learn. Res., 99:1663–1707, August 2010.
  9. B. Goethals, S. Laur, H. Lipmaa, and T. Mielik?inen. On private scalar product computation for privacy-preserving data mining.In In Proceedings of the 7th Annual International Conference in Information Security and Cryptology, pages 104–120. Springer-Verlag,2004.
  10. L. Kissner and D. Song. Privacy-preserving set operations. InIN ADVANCES IN CRYPTOLOGY – CRYPTO 2005, LNCS, pages241–257. Springer, 2005.
  11. 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.
  12. 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
  13. R. J. Michael Hart and A. Stent. More content – less control: Access control in the web 2.0. In Proceedings of the Workshop on Web 2.0 Security and Privacy at the IEEE Symposium on Security and Privacy, 2007.
  14. E. Newman. The structure and function of complex networks. SIAM review, 45(2):167–256, 2003.
  15. L. Plane. Unpacking privacy for a networked world. Pages 129–136. Press, 2003.