The Privacy Tools project develops open access course materials and videos on data privacy from a variety of disciplinary perspectives.
A full list of courses is available here.
The Privacy Tools project develops open access course materials and videos on data privacy from a variety of disciplinary perspectives.
A full list of courses is available here.
Course Description: This course focuses on information as quantity, resource, and property. We study the application of quantitative methods to understanding how information technologies inform issues of public policy, regulation, and law. How are music, images, and telephone conversations represented digitally, and how are they moved reliably from place to place through wires, glass fibers, and the air? Who owns information, who owns software, what forms of regulation and law restrict the communication and use of information, and does it matter? How can personal privacy be protected at the same time that society benefits from communicated or shared information?
The recorded lectures are from the Harvard Faculty of Arts and Sciences course Quantitative Reasoning 48, which was offered as an online course at the Extension School. The Quicktime and MP3 formats are available for download, or you can play the Flash version directly.
Course Materials: View all lectures related to privacy
If you are a practicing social scientist, Micah Altman's course "Managing Confidential Data" may be on interest. Below is information on the course, including slides.
Course: "Managing Confidential Data”"
Professor: Micah Altman
Course Description: This tutorial provides a framework for identifying and managing confidential information in research. It is most appropriate for mid-late career graduate students, faculty, and professional research staff who actively engage in the design/planning of research. The course will provide an overview of the major legal requirements governing confidential research data; and the core technological measures used to safeguard data. And it will provide an introduction to the statistical methods and software tools used to analyze and limit disclosure risks. Failures of confidentiality threaten research integrity, reputation, legality, and funding. Every researcher in the social, behavioral and health sciences must understand how to manage confidential information in research. Successful management of confidential information is particularly challenging because it requires satisfying a combination of complex legal, statistical and technological constants. And the management of this information has grown increasingly challenging because of recent changes in the law, new forms of data collection, and advances in statistical methods for linking data. Course materials for "Managing Confidential Information" are available here.
This course was offered twice in 2015 and once so far in 2016.
Course Website: http://informatics.mit.edu/classes/managingconfidentialdata
Course Materials: http://www.slideshare.net/slideshow/embed_code/21164359
Below is a tutorial video of co-PI Micah Altman presenting "Managing Confidential Data," from our Summer Interns' Orientation (Summer 2015)
The syllabus, readings, and homework assignments are available on the course website.
The syllabus, reading list, and homework assignments are available on the course website.
Course: CS 208: Applied Privacy for Data Science (Spring 2019)
Instructors: James Honaker and Salil Vadhan
The syllabus, reading list, and homework assignments are available on the course website
Ori Heffetz and Katrina Ligett, Privacy and Data-Based Research
Kobbi Nissim, Thomas Steinke, Alexandra Wood, Mark Bun, Marco Gaboardi, David R. O'Brien, and Salil Vadhan, Differential Privacy: A Primer for a Non-technical Audience (Preliminary Version)
Daniel Muise and Kobbi Nissim, Differential Privacy in CDFs
Collaborator Cynthia Dwork, A Firm Foundation for Private Data Analysis
Professor: Salil P. Vadhan
Course Description: Algorithms to guarantee privacy and authenticity of data during communication and computation. Rigorous proofs of security based on precise definitions and assumptions. Topics may include one-way functions, private-key and public-key encryption, digital signatures, pseudorandom generators, fully homomorphic encryption, and the role of cryptography in network and systems security.
Fall 2013 and fall 2006 lecture notes, videos, and homework assignments are available on the course website.
Project Tutorial, Salil Vadhan (38:58 mins) | Dataverse Overview, James Honaker (36:22 mins) |
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Legal Overview, Alexandra Wood (18:03 mins) |
DataTags Demo, Michael Bar-Sinai and Alexandra Wood (42:59 mins) |
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Managing Confidential Data, Micah Altman (40:26 mins) | Differential Privacy (nontechnical), Salil Vadhan (50:44 mins) |
R Tutorial, James Honaker (1:13:40 mins) | Differential Privacy (technical), Kobbi Nissim (1:08:29 mins) |