Almaden Institute

Privacy Preservation to Enable Data Mining Across Enterprises Abstract: The confluence of data mining, large databases, and networked information sources opens a wealth of possibilities for knowledge discovery. Privacy and security concerns have led to a backlash against these technologies: witness street protests in Japan in August 2002 over the creation of a national registry and ID number, and the introduction in the U.S. Senate of the “Data-Mining Moratorium Act of 2003.” The irony is that most data mining generates summary results that do not violate privacy. Are we simply facing a need to educate the public on what data mining really is? The answer is no: the problem is real. It isn’t data mining that is at fault, but gathering the data into a common warehouse to enable data mining. This talk will discuss how privacy-preserving data mining can enable applications that might otherwise be prevented due to privacy concerns. Examples will be presented from both public and private sector, along with a summary of techniques not covered in preceding talks.   Chris Clifton - Bio  Chris Clifton  Associate Professor of Computer Science  Purdue University  clifton@cs.purdue.edu  Web Sites  http://www.cs.purdue.edu/people/clifton Biography Chris Clifton is an Associate Professor of Computer Science at Purdue University. He has a Ph.D. from Princeton University, and Bachelor’s and Master’s degrees from the Massachusetts Institute of Technology. Prior to joining Purdue in 2001, Chris had served as a Principal Scientist at The MITRE Corporation and as an Assistant Professor of Computer Science at Northwestern University. His research interests include data mining, data security, database support for text, and heterogeneous databases.