Organizations collect vast amounts of information on individuals, and at the same time they have access to ever-increasing levels of computational power. Although this conjunction of information and power provides great benefits to society, it also threatens individual privacy. Privacy and individuals’ anonymity is of paramount importance in data mining field, since it is easier than ever to infer sensitive information using a combination of data mining techniques. The data mining practitioners and researchers should ensure that the privacy aspects of the analyzed data are being addressed.

The PAIS’17 Workshop will provide an open yet focused platform for researchers and practitioners from computer science and other fields that are interacting with computer science in the data privacy area such as statistics, healthcare informatics, and law to discuss and present current research challenges and advances in data privacy and anonymity research. We welcome original research papers that present novel research ideas, position papers that discuss new technology trends and provide new insights into this area, integrative papers that present interdisciplinary research in the privacy area, as well as industry papers that share practical experiences.