Privacy – Algorithmic Foundations and Usability (Sommersemester 2017)

Dozent: Prof. Dr. Christoph Meinel (Internet-Technologien und -Systeme)
Tutoren: Dr. Anne Kayem

Allgemeine Information

Semesterwochenstunden: 4
ECTS: 6
Benotet: Ja
Einschreibefrist: 28.04.2017
Lehrform: Vorlesung / Seminar
Belegungsart: Wahlpflichtmodul

Studiengänge, Modulgruppen & Module

IT-Systems Engineering MA

IT-Systems Engineering
- HPI-ITSE-A Analyse
IT-Systems Engineering
- HPI-ITSE-E Entwurf
IT-Systems Engineering
- HPI-ITSE-K Konstruktion
IT-Systems Engineering
- HPI-ITSE-M Maintenance
ISAE: Internet, Security & Algorithm Engineering
- HPI-ISAE-S Spezialisierung
ISAE: Internet, Security & Algorithm Engineering
- HPI-ISAE-T Techniken und Werkzeuge

Beschreibung

Statistics estimate that as many as 350 million photographs are shared daily on Facebook, and more than 500 million tweets on Twitter. Large volumes of information are an important source of information for data analytics operations for instance, but also raise justified user concerns about personal information disclosure. Studies indicate that it is possible, to discover behaviours (that are even unknown to users themselves) by combining information drawn from multiple datasets.

In this course, we consider the problem of privacy preserving algorithm design and reflect on the growing recognition that algorithmic approaches alone are not an adequate solution. As a first step, we study some existing privacy preserving algorithms from the principles of operation (protection and performance). We follow this in the second step by studying methods of enabling users expressively control disclosure, and consider the role human factors play in the success and/or failure of privacy systems. Using a case study approach, we study a variety of privacy systems and design studies to evaluate the usability issues.

The course will be conducted in a mixed lecture/seminar style in which the first series of lecture slots wil be dedicated to presenting background material required to support participants in preparing for the presentation, and compiling a portfolio. A choice of presentation topics can be found here, and participants may indicate topic preferences (here). Topic assignments will occur in Week 4.

Each participant will be expected to prepare a presentation, and compile a portfolio, based on the topic he/she is assigned.

Lectures will be centered on the following topics:

Challenges in quantifying privacy, and usability
Authentication - Privacy and Usability Considerations
Web-Based Privacy Enhancing Technologies
Attacks to Privacy
Making Privacy and Anonymity Tools Usable
Protecting publicly shared data
Privacy Protection - Design and Human Factor Considerations

Voraussetzungen

This course is suitable for participants who are interested in security and privacy, but who would like to learn more about usability; and for those interested in usability but who would like to learn about security and privacy. In addition having a combination of the following skills would be helpful:

Software Development in Java, C/C++, or Python
Some experience with designing user studies

Literatur

Ming Cheung and James She. 2016. "Evaluating the Privacy Risk of User-Shared Images". ACM Trans. Multimedia Comput. Commun. Appl. 12, 4s, Article 58 (September 2016)
Allison Woodruff, Vasyl Pihur, Sunny Consolvo, Lauren Schmidt, Laura Brandimarte, and Alessandro Acquisti. "Would a Privacy Fundamentalist Sell Their DNA for $1000...If Nothing Bad Happened as a Result? The Westin Categories, Behavioural Intentions, and Consequences." In Proceedings of the Tenth Symposium on Usable Privacy and Security, 2014.
Scott Ruoti, Nathan Kim, Ben Burgon, Timothy van der Horst, Kent Seamons. "Confused Johnny: When Automatic Encryption Leads to Confusion and Mistakes". In Proceedings of the Ninth Symposium on Usable Privacy and Security, 2013.
"Research Methods in Human Computer Interaction", by Jonathan Lazar, Jinjuan Heidi Feng, Harry Hochheiser

Additional reading material will be provided online or handed out in class.

Leistungserfassung

The final course grade will be based on:

50% Portfolio

30% Presentation

20% Final Exam

Portfolio: The portfolio will comprise the documentation collected to support the presentation. This should include at least some combination of the following - your presentation proposal, user consent form (a template will be provided), reference material consulted, studies conducted (e.g. questionnaires, survey, interviews, prototypes, etc.) to support hypotheses, and experiments. Your portfolio should describe progress made, problems encountered, and how the problems were addressed. Details of the pilot user studies (initial study, design, prototype, scripts, code/implementations, results...) should also be included.

Presentation: Each participant will be assigned a topic on which he/she will work individually. Topic choices can be made here. Individual weekly meetings will provide an opportunity to discuss matters, related to the presentation topics, and for which advice is required.

Final Exam: Open Book or Oral.