Monday, March 17, 2008
11:00 AM
Computer Studies Bldg. Room 209
Daniel Golovin
Carnegie Mellon University
Uniquely Represented Data Structures with Applications to Privacy
A uniquely represented data structure has a unique physical state to encode each logical state of its abstract data type. In this talk I will discuss new efficient uniquely represented versions of popular data structures (including hash tables, binary search trees, and queues), how these data structures work, and how they can be used to improve the security and privacy of real-world applications.

As an example application, consider a typical system with some internal data structures. If the memory representations of those internal data structures are inspected, they may leave significant clues to the past use of the system. For example, a data structure with lazy deletions might retain an object that the user believes was deleted long ago; this is problematic in environments requiring high security or strict privacy guarantees. Uniquely represented data structures eliminate such problems entirely by storing exactly the information specified by an abstract data type, and nothing more.

Bio: Daniel Golovin is a Ph.D. candidate at Carnegie Mellon University under the supervision of Guy Blelloch. His research interests include approximation and online algorithms, using novel data structures to improve privacy, and provably good ways of dealing with uncertainty. He received his B.S. from Cornell University in 2003 and his M.S. from Carnegie Mellon University in 2006.

Refreshments will be served at 10:45