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For further details contact:

N.RAJASEKARAN B.E M.S 9841091117,9840103301.

IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com

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17

  1. 1. Impulse Technologies Beacons U to World of technology 044-42133143, 98401 03301,9841091117 ieeeprojects@yahoo.com www.impulse.net.in Preventing Private Information Inference Attacks on Social Networks Abstract Online social networks, such as Face book, are increasingly utilized by many people. These networks allow users to publish details about themselves and to connect to their friends. Some of the information revealed inside these networks is meant to be private. Yet it is possible that corporations could use learning algorithms on released data to predict undisclosed private information. In this paper, we explore how to launch inference attacks using released social networking data to predict undisclosed private information about individuals, such as their political affiliation or sexual orientation. We then devise three possible sanitization techniques that could be used in various situations. Then, we explore the effectiveness of these techniques by implementing them on a dataset obtained from a specific geographical region of the Face book social networking application and attempting to use methods of collective inference to discover sensitive attributes of the data set. We show that we can decrease the effectiveness of both local and relational classification algorithms by using the sanitization methods we described. Your Own Ideas or Any project from any company can be Implementedat Better price (All Projects can be done in Java or DotNet whichever the student wants) 1

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