There is an inherent trade-off between the utility that databases can offer and the privacy they afford to their constituents. As a part of our algorithmic and theoretical researches in data privacy, we are studying this trade-off formally, attempting to understand the relationship between privacy and utility. On a practical side, we are also building an industrial scale product in this domain that can address the real world problems.
In this talk, I will mention some important scenarios in this arena, point out a few open problems and discuss our jabs at them. I will also introduce Masketeer, our data masking product, that can be useful in generating test-beds from production data.
Sachin Lodha did his undergraduate studies in Computer Science and Engineering at Indian Institute of Technology, Bombay between 1992-96. He got his PhD under Professor Endre Szemer\350di at Rutgers in 2002.
Since then, Sachin is working as a scientist at Tata Research Development and Design Centre (TRDDC), a research unit of Tata Consultancy Services Ltd. He is broadly interested in the design and analysis of algorithms, with an emphasis on on-line algorithms and approximation algorithms, graph theory and combinatorics. Currently, he is heading research in data privacy at TRDDC where the ultimate goal is to find solutions that provide the right balance between the extremes of fully disclosed and completely withheld data.
Gates 4B (opposite 490)