Privacy Policy Inference of User-Uploaded Images on Content Sharing Sites

Author(s):

D.Banupriya , Shrimati Indira Gandhi College, Trichy; Mrs. V. Vetriselvi, Shrimati Indira Gandhi College, Trichy

Keywords:

Adaptive Privacy Policy Prediction (A3P), A3P- Core, A3P- Social, Polar Fourier Transform (PFT)

Abstract:

Social Network is an emerging E-service for content sharing sites (CSS). It is emerging service which provides a reliable communication, through this communication a new attack ground for data hackers; they can easily misuses the data through these media. Some users over CSS affects users privacy on their personal contents, where some users keep on sending unwanted comments and messages by taking advantage of the users’ inherent trust in their relationship network. By this privacy of the user data may be loss for this issue this paper handles the most prevalent issues and threats targeting different CSS recently. This proposes a privacy policy prediction and access restrictions along with blocking scheme for social sites using data mining techniques. To perform this, the system utilizes APP (Access Policy Prediction) and Access control mechanism by applying BIC algorithm (Bayesian Information Criterion).

Other Details:

Manuscript Id	:	IJSTEV2I12217
Published in	:	Volume : 2, Issue : 12
Publication Date	:	01/07/2016
Page(s)	:	593-597

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