Carnegie Mellon University

CMU Data Privacy Center

Privacy and Anonymity in Data


CS 15-394 / CALD 10-711 / ISRI 17-802

Professor: Latanya Sweeney, Ph.D., latanya@dataprivacylab.org
TAs: Edoardo Airoldi, edota@dataprivacylab.org
Yiheng Li, yihengta@dataprivacylab.org
Joao Sousa, jpsousata@dataprivacylab.org
Lecture: Tuesdays and Thursdays, 3:00-4:20pm, Wean 5419ab
Office Hours:

Prof. Sweeney, 5-6pm on Tuesdays and Thursdays, Wean 1301
Edoardo Airoldi, contact edota@dataprivacylab.org
Yiheng Li, contact yihengta@dataprivacylab.org
Joao Sousa, contact jpsousata@dataprivacylab.org
or contact Sherice Livingston at sherice@andrew.cmu.edu to make an appointment with Prof. Sweeney
Links: Schedule, Handouts, Syllabus


Course Description

This course introduces students to concepts and methods for creating technologies and related policies with provable guarantees of privacy protection while allowing society to collect and share person-specific information for many worthy purposes. Methods include those related to the identifiability of data, record linkage, data profiling, data fusion, data anonymity, de-identification, policy specification and enforcement and privacy-preserving data mining. Students get hands-on experience at being "data detectives" and acquire knowlege from publicly available information by building dossiers and identifying individuals from seemingly anonymous or innocent data. Conversely, students also learn to be "data protectors" by developing and assessing privacy protocols, algorithms and anonymity protection schemes to protect inferences in shared data. Students learn a 6-prong approach at assessing and constructing technologies that are provably fit for a stated purpose in a social-legal-organizational setting. Emerging technologies examined include: face recognition software, biometrics, survillance systems, personal information capturing tools and position location technology (GPS, E911 telephones, IR tags). Related topics are drawn from: data mining, information retrieval, web technology, computer security, cryptography, relational databases, statistics and political philosophy.

Contact Information

Course web site: https://dataprivacylab.org/courses/pad1/index.html
Email discussion: pad@dataprivacylab.org


Course Links


Handouts and books

There is no required textbook for this course. Instead, we will provide course copies and working papers as the course progresses. Handouts will also be available at the course web site.


Related links at (CMU):


Fall 2003 Data Privacy Course [webmaster@dataprivacylab.org] Last revised 1/2004 Latanya Sweeney