Effective Query Log Anonymization

Google Tech Talks December 8, 2008 ABSTRACT User search query logs have proven to be very useful, but have vast potential for misuse. Several incidents have shown that simple removal of identifiers is insufficient to protect the identity of users. Publishing such inadequately anonymized data can cause severe breach of privacy. While significant effort has been expended on coming up with anonymity models and techniques for microdata/relational data, there is little corresponding work for query log data -- which is different in several important aspects. In this work, we take a first cut at tackling this problem. Our main contribution is to define effective anonymization models for query log data, along with techniques to achieve such anonymization. Speaker: Dr. Jaideep Vaidya Dr. Jaideep Vaidya is an Assistant Professor at Rutgers University. He received his Masters and Ph.D. at Purdue University and his Bachelors degree at the University of Mumbai. His research interests are in Data Mining, Privacy, Security, and Information Sharing. He has published over 30 papers in international conferences and archival journals, and has received two best paper awards from the premier conferences in data mining and databases. He is also the recipient of a NSF Career Award and is a member of the ACM, and the IEEE Computer Society.