Preventing Private Information Inference Attacks on Online Social Networks
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 8
Abstract
On-line social networks like Facebook are increasingly utilized by many people. These networks allow users to publish their own details and enable them to contact their friends. Some of the information revealed inside these networks is private. But it is possible that corporations could use learning algorithms on released data to predict undisclosed private information. In this work, ways to launch inference attacks are explored using released social networking data to predict unrevealed private information about personalities. Then three possible sanitization techniques that could be used in various situations are devised.The effectiveness of these techniques are evaluated by implementing them on a dataset.
Authors and Affiliations
Ramya R
Keywords
Related Articles
- EP ID EP22536
- DOI -
- Views 198
- Downloads 6
Exogenous Foliar Application of Phenolic Acids on Quality Constituents of Tea
Exogenous foliar application of phenolic acid could alter the biochemical composition and enhance the antioxidant potential there by protect the living organisms from oxidative injuries. Though the reports on foliar app...
Interface to Database By Using English Language
Information is playing an important role in our lives. One of the major sources of information is databases. Databases and database technology are having major impact on the growing use of computers. Almost all IT appli...
Revenue and Profit Maximization of Intermediary by Providing Multiple Cloud Services to Users
Data streaming with various cloud condition is a potential response for give the profitable pay on demand respond in due order regarding tradeoff between whole deal leasing and contrasting burdens. In this paper, we pro...
Review on Smoothed Particles Hydrodynamics Simulation and Rendering
Smoothed Particle Hydrodynamics (SPH), a computational method for simulating fluid flows is easily parallelizable, as the interaction between two particles is independent of the others. For high quality conception at ve...
Low Area and Low Power CMOS technology based RAM and Ternary CAM memory design
Ternary content addressable memory (TCAM) is an associative memory or associative array for very high speed searching applications. It compares input search data (tag) against a table of stored data and returns the addr...