This book investigates the complex challenges and evolving methodologies for ensuring data privacy within statistical databases. It compiles research presented at the 2010 conference in Kerkyra, Greece, focusing on the tension between data utility and individual privacy. The contributions explore various techniques, including differential privacy, k-anonymity, and secure multi-party computation, to safeguard sensitive information while enabling valuable statistical analysis.

This volume represents a collection of academic papers from a specialized conference, indicating a focus on theoretical and technical aspects of statistical database privacy. The content likely appeals to researchers, computer scientists, and data security professionals seeking in-depth knowledge of current privacy-preserving techniques. The discussions are expected to be rigorous, addressing complex algorithmic and mathematical challenges in the field.