Tuesday, November 22, 2011

Freeing Cloud Databases from Privacy Constraints

Professor Chris Clifton, Purdue University, will speak on "Freeing Cloud Databases from Privacy Constraints" at the Australian National University, in Canberra, 4pm 28 November 2011.

Freeing Cloud Databases from Privacy Constraints

Assoc Prof Chris Clifton (Purdue University )

COMPUTER SCIENCE SEMINAR

DATE: 2011-11-28
TIME: 16:00:00 - 17:00:00
LOCATION: CSIT Seminar Room, N101
CONTACT: peter.christen@anu.edu.au

ABSTRACT:
Privacy regulations can constrain how data is managed, particularly trans-border sharing and storage of data. This has significant implications for the use of cloud databases to manage private data. While management of encrypted data has received some research attention, this limits the services that can be provided by a cloud database. We propose to instead encrypt only the link between identifying data and sensitive information, thus eliminating the "individually identifiable" aspect of data that triggers most privacy regulations. This frees the cloud database to provide value-added services such as data cleansing and data analysis without constraint of privacy regulations.

This talk will discuss our early results in this area, including schema development (how do we ensure that sensitive information cannot be identified?) and query processing (how do we handle the fact that part of the data needed to process the query is encrypted, and only the client has the key?) In addition to our existing results, we will discuss ongoing work, including the challenges posed by database systems designed specifically for cloud computing.
BIO:
Dr. Clifton works on data privacy, particularly with respect to analysis of private data. This includes privacy-preserving data mining, data de-identification and anonymization, and limits on identifying individuals from data mining models. He also works more broadly in data mining, including data mining of text and data mining techniques applied to interoperation of heterogeneous information sources. Fundamental data mining challenges posed by these applications include extracting knowledge from noisy data, identifying knowledge in highly skewed data (few examples of "interesting" behavior), and limits on learning. He also works on database support for widely distributed and autonomously controlled information, particularly issues related to data privacy.

Prior to joining Purdue in 2001, Dr. Clifton was a principal scientist in the Information Technology Division at the MITRE Corporation. Before joining MITRE in 1995, he was an assistant professor of computer science at Northwestern University. He has a Ph.D. (1991) and M.A. (1988) from Princeton University, and Bachelor's and Master's degrees (1986) from the Massachusetts Institute of Technology.

URL: http://www.cs.purdue.edu/people/faculty/clifton/

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