Privacy is essential for the provision of electronic and knowledge-based services in modern e-business, e-commerce, e-government, and e-health environments. Nowadays, service providers can easily track an individual's actions, behaviors, and habits. Given large data collections of person-specific information, providers can data mine to learn patterns, models, and trends that can be used to provide personalized services. The potential benefits of data mining are substantial, but it is evident that the collection and analysis of sensitive personal data arouses concerns about citizens' privacy, confidentiality and freedom.

When addressed at a technical level, privacy-awareness fosters the dissemination and adoption of emerging knowledge-based applications. Obtaining the potential benefits of data mining with a privacy-aware technology can enable a wider social acceptance of a multitude of new services and applications based on the knowledge discovery process. Source data of particular importance include, for instance, biomedical patient data, web usage log data, mobility data from wireless and sensor networks: in each case there exist substantial privacy threats, as well as a potential usefulness of knowledge discovered from these data.

Privacy protection in data mining is a crucial issue that has captured the attention of many researchers and administrators across a large number of application domains. Despite such efforts there are still many open issues that deserve further investigation. The workshop hopes to gather researchers and practitioners interested in the privacy aspects of data mining, both by a technical, and a social and legal point of views. We hope to attract interest from a wide range of possible data mining subareas, including: web mining, medical data mining, spatio-temporal data mining, ubiquitous knowledge discovery, and obviously, privacy-preserving data mining.