CS 573 Data Privacy and Security, Spring 2009

Lecture: TuTh 10:00-11:15am MSC W302

Web: http://www.mathcs.emory.edu/~CS573000
Mailing List: CS573000-list@mathcs.emory.edu
Share Directory: /home/CS573000/share

Instructor: Li Xiong (lxiong@mathcs.emory.edu)
Office Hours: TT 2-3pm at MSC E412 or by appointment
TA: James Gardner (jgardn3@emory.edu)

Overview

The huge amount of individual data collected daily by various agencies (such as personal medical records and personal finance information) is of great value for our society. However, they also pose a significant threat to individuals’ privacy. At the technology side, computational solutions and protocols are being developed for protecting individual privacy and securing the personal data. This course will introduce students to the concepts and technologies for privacy protection while allowing society to collect and share person-specific data for many worthy purposes. The main topics include privacy and anonymity models, data anonymization, statistical databases, privacy-preserving data mining, privacy in social networks, etc. The foundations are drawn from a number of sub-disciplines of Computer Science including: database systems, data mining, information retrieval, computer security, cryptography, and statistics.

Readings

There is no textbook for the course. We will mainly read papers.

Prerequisites

There are no prerequisites. Familiarity with a programming language, such as Java or C++, is required for programming assignments and/or final project. Some knowledge about database systems and statistics will be helpful.

Assignments

There will be reading assignments, paper presentations, case studies, and programming assignments. For reading assignments, you will read papers and submit a written review. You are expected to present one paper in class. For case studies, you will be provided with some available datasets and play "data detectives" and acquire knowledge from these datasets by identifying individuals from seemingly anonymous or innocent data. For programming assignments, you will be implementing some existing privacy preserving data publishing or data mining algorithms.

Exams

There will be one open-book midterm exam. There will be no final exam.

Project

There will be a substantial course project. Different project ideas and options will be discussed and posted. Project deliverables include project proposal, in-class project presentation, project report, source code and executable package if applicable.

Grading

Component Weight
Assignments and presentations40
Midterm30
Project30
Score Grade
93-100 A
90-92.9 A-
87-89.9 B+
83-869 B
80-82.9 B-
Enjoy yourself and good luck!