Volume 2, Issue 3, September 2017, Page: 78-85
Secrecy of Uploaded Images on Locates Using A3P Algorithm
Sivanantham Sivakumar, Department of Information Technology, Adhiyamaan College of Engineering, Hosur, Tamil Nadu, India
Musrathasleema Abdul Rahman, Department of Information Technology, Adhiyamaan College of Engineering, Hosur, Tamil Nadu, India
Nandhini Balu, Department of Information Technology, Adhiyamaan College of Engineering, Hosur, Tamil Nadu, India
Nivetha Nainar, Department of Information Technology, Adhiyamaan College of Engineering, Hosur, Tamil Nadu, India
Received: Feb. 13, 2017;       Accepted: Mar. 15, 2017;       Published: Mar. 29, 2017
DOI: 10.11648/j.mlr.20170203.11      View  1529      Downloads  57
Abstract
With increasing volume of images users share through social sites, maintaining privacy has become a major problem, as demonstrated by a recent wave of publicized incidents where users individually shared personal information. In light of these incidents, the need of tools to help users control access to their shared content is apparent. Toward addressing this need, we propose an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. We examine the role of social context, image content and metadata as possible indicators of user’s privacy preferences. We propose a two-level framework which according to the user’s available history on the site, determines the best available privacy policy for the user’s images being uploaded. Our solution relies on an image classification framework for images categories which may be associated with similar policies on a policy prediction algorithm to automatically generate a policy for each newly uploaded image and also according to user’s social features. Over time, generated policies will follow the evolution of user’s privacy attitude.
Keywords
Content Sharing Sites, Privacy, Metadata, A3P, Social Media
To cite this article
Sivanantham Sivakumar, Musrathasleema Abdul Rahman, Nandhini Balu, Nivetha Nainar, Secrecy of Uploaded Images on Locates Using A3P Algorithm, Machine Learning Research. Vol. 2, No. 3, 2017, pp. 78-85. doi: 10.11648/j.mlr.20170203.11
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
S. Ahern, D. Eckles, N. S. Good, S. King, M. Naaman, and R. Nair, “Over-exposed? Privacy patterns and considerations in online and mobile photo sharing,” in Proc. Conf. Human Factors Comput. Syst., 2007, pp. 357–366.
[2]
Y. Liu, K. P. Gummadi, B. Krishnamurthy, and A. Mislove, “Analyzing facebook privacy settings: User expectations vs. reality,” inProc. ACMSIGCOMM Conf. Internet Meas. Conf., 2011, pp. 61–70.
[3]
S. Jones and E. O’Neill, “Contextual dynamics of group-based sharing decisions,” in Proc. Conf. Human Factors Comput. Syst., 2011, pp. 1777–1786. [Online]. Available: http://doi.acm.org/ 10.1145/1978942.1979200.
[4]
A. Acquisti and R. Gross, “Imagined communities: Awareness, information sharing, and privacy on the facebook,” in Proc. 6th Int. Conf. Privacy Enhancing Technol. Workshop, 2006, pp. 36–58.
[5]
L. Church, J. Anderson, J. Bonneau, and F. Stajano, “Privacy stories: Confidence on privacy behaviors through end user programming,” in Proc, 2009, 5th Symp. Usable Privacy Security.
[6]
H. Lipford, A. Besmer, and J. Watson, “Understanding privacy settings in facebook with an audience view,” in Proc. Conf. Usability, Psychol., Security, 2008.
[7]
K. Strater and H. Lipford, “Strategies and struggles with privacy in an online social networking community,” in Proc. Brit. Comput. Soc. Conf. Human-Comput. Interact, 2008, pp. 111–119.
[8]
J. Bonneau, J. Anderson, and L. Church, “Privacy suites: Shared privacy for social networks,” in Proc. Symp. Usable Privacy Security, 2009.
[9]
A. Mazzia, K. LeFevre, and A. E., “The PViz comprehension tool for social network privacy settings,” in Proc. Symp. Usable Privacy Security, 2012.
[10]
R. Ravichandran, M. Benisch, P. Kelley, and N. Sadeh, “Capturing social networking privacy preferences,” in Proc. Symp. Usable Privacy Security, 2009.
[11]
A. Besmer and H. Lipford, “Tagged photos: Concerns, perceptions, and protections,” in Proc. 27th Int. Conf. Extended Abstracts Human Factors Comput. Syst., 2009, pp. 4585–4590.
[12]
C. A. Yeung, L. Kagal, N. Gibbins, and N. Shadbolt, “Providing access control to online photo albums based on tags and linked data,” in Proc. Soc. Semantic Web: Where Web 2.0 Meets Web 3.0 at the AAAI Symp., 2009, pp. 9–14.
[13]
M. Ames and M. Naaman, “Why we tag: Motivations for annotation in mobile and online media,” in Proc. Conf. Human Factors Comput. Syst., 2007, pp. 971–980.
[14]
G. Loy and A. Zelinsky, “Fast radial symmetry for detecting points of interest,” IEEE Trans. Pattern Anal. Mach. Intell. 2003, vol. 25, no. 8, pp. 959–973, Aug.
[15]
D. G. Lowe, (2004, Nov.). Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. [Online]. 60 (2), pp. 91–110. Available: http://dx.doi.org/10.1023/B: VISI.0000029664.99615.
Browse journals by subject