CMSC 818C: Local Data and User Privacy

Spring 2012

General Course Information

Instructor: Bobby Bhattacharjee
bobby@cs.umd.edu
4143  A. V. Williams Building
Office Hours: Wednesday 11:00 a.m. -- 12:00 p.m. 
E-mail is the easiest and fastest way to contact me.
Please put the string "CMSC 818C: " somewhere in the subject line of your message
Room and Time: 3118  Computer Science Instruction Center
Tuesdays and Thursdays 12:30 p.m. -- 1:45 p.m.

Introduction

We will cover classic and recent work in two broad research topics in computer systems: local data and user privacy.

Local data refers to information that is available without accessing a wide-area network. Local data can be gathered by environmental sensors or generated by users, and is usually 'tagged' with context such as location and time. As part of this course, we will concentrate on systems and protocols for small form-factor computing devices, e.g. smart phones and tablets, that enable spontaneous and opportunistic gathering and dissemination of local data. Topics will include overall system design, data delivery models, principals and naming, content-based routing, and application areas.

The user privacy component of the course will consider social implications of local computing. The current Internet economic model uses user data as the currency for "free" services such as social networks and web-based email. These services have percolated down to personal devices, increasing detail in the information (potentially) leaked. We will study protocols that quantify information leakage in different settings, and systems that attempt to provide useful service without revealing personal information. Topics will include designing systems ground-up for user privacy, incentive-models for encouraging privacy, and economic models for valuating private information.

Grading

You will be graded on class participation, presentations, and on a single semester project.

Credits

This course cannot be used for Ph.D. CORE credit. However, if you are a Masters student, you may base your Master thesis/scholarly paper on your work.