/* This is the template for project details pages */

/* 
  The database entry:
  "type" is one of the following: phd theses, phd semester, master thesis, master semester, bachelor semester
  "state" is one of the following: available, taken, completed (please upgrade accordingly!!!!!!!!!!) 
  "by" should be filled as soon as the project is taken/completed
  "completed_dt" is the date when the project was completed (YYYY-MM-DD). 
  "output_media" is the link to the pdf of the project (wiki syntax)
  "table" must be "projects" => don't touch it!
*/
---- dataentry project ----
title : Differential Privacy for Social Networks
contactname: Lyudmila Yartseva
contactmail_mail: lyudmila.yartseva@epfl.ch
contacttel: 31343
contactroom: BC148
type : master semester
state : unavailable
created_dt :  2011-09-26
taken_dt : YYYY-MM-DD
completed_dt : YYYY-MM-DD
by : the full name of the student
output_media : en:projects:mahdi_thesis.pdf|Download Mahdi's Thesis
table : projects
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template:datatemplates:project
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/* Description of the project */
For the purpose of government and scientific research of social networks, it is desirable to have possibilities to reveal the information about a Social Network's structure.
Applying a small amount of random modifications to the social network before publishing its structure or some aggregate characteristic is a common approach to preserving privacy. It is called anonymization.
In the realm of relational databases, the notion of differential privacy is used as a means to measure the amount of utility of various characteristics of the database that is preserved by such changes.

The goal of the project is to extend the definition of differential privacy to Social Networks. In particular, to find proper measures of the information loss during anonymization.

Requirements: Solid Probability theory background, Graph theory, Random graphs desirable.