Login | Register

Models and Algorithms for Private Data Sharing


Models and Algorithms for Private Data Sharing

Mohammed, Noman (2012) Models and Algorithms for Private Data Sharing. PhD thesis, Concordia University.

[thumbnail of Mohammed_PhD_F2012.pdf]
Text (application/pdf)
Mohammed_PhD_F2012.pdf - Accepted Version


In recent years, there has been a tremendous growth in the collection of digital information about individuals. Many organizations such as governmental agencies, hospitals, and financial companies collect and disseminate various person-specific data. Due to the rapid advance in the storing, processing, and networking capabilities of the computing devices, the collected data can now be easily analyzed to infer valuable information for research and business purposes. Data from different sources can be integrated and further analyzed to gain better insights. On one hand, the collected data offer tremendous opportunities for mining useful information. On the other hand, the mining process poses a threat to individual privacy since these data often contain sensitive information. In this thesis, we address the problem of developing anonymization algorithms to thwart potential privacy attacks in different real-life data sharing scenarios. In particular, we study two privacy models: LKC-privacy and differential privacy. For each of these models, we develop algorithms for anonymizing different types of data such as relational data, trajectory data, and heterogeneous data. We also develop algorithms for distributed data where multiple data publishers cooperate to integrate their private data without violating the given
privacy requirements. Experimental results on the real-life data demonstrate that the proposed anonymization algorithms can effectively retain the essential information for data analysis and are scalable for large data sets.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (PhD)
Authors:Mohammed, Noman
Institution:Concordia University
Degree Name:Ph. D.
Program:Computer Science
Date:5 July 2012
ID Code:974480
Deposited On:29 Oct 2012 19:37
Last Modified:18 Jan 2018 17:38
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top