Privacy Preserving Data Mining Using PiecewiseVector Quantization
Abstract
Most content sharing websites allow users to enter their privacy preferences. Unfortunately, recent studies have shown that users struggle to set up and maintain such privacy settings. In this paper, we propose an Adaptive Privacy Policy Prediction (A3P) system which aims to provide users a hassle free privacy settings experience by automatically generating personalized policies. The A3P system handles user uploaded images, and factors in the following criteria that influence one’s privacy settings of images. We design the interaction flows between the two building blocks to balance the benefits from meeting personal characteristics and obtaining community advice. Keywords- PPDM, Vector Quantization, A3P, Data Mining, APP, Prediction.
Full Text PDF
IMPORTANT DATES
Submit paper at ijasret@gmail.com
Paper Submission Open For |
March 2024 |
UGC indexed in (Old UGC) |
2017 |
Last date for paper submission |
30th March, 2024 |
Deadline |
Submit Paper any time |
Publication of Paper |
Within 01-02 Days after completing all the formalities |
Paper Submission Open For |
Publication /online Conference |
Publication Fees |
Free for PR Students
|
|