Secure Multiparty Computation (SMC) is a universally applicable privacy-enhancing technology, that can be used whenever untrusted platforms compute on sensitive data. These theoretical possibilities of SMC have been known for a long time, and the last 5-7 years have seen further impressive theoretical advances in this field. These have been accompanied with some practical applications, but these have been small in number and restricted to a couple of fields. With this workshop, we want to bring together researchers of SMC and builders of secure systems, to discuss the secure computation techniques necessary for practical applications. We are interested in practical experience of applying SMC (both positive and negative), privacy-preserving methods of solving particular problems, the integration of SMC with the rest of a secure system and any positive and negative interplay it may have with other functional and non-functional requirements, emerging problems in applications made possible by SMC, etc.

Topics of interest of this workshop include, but are not limited to:

Experience in applying SMC;
SMC and big data;
Design of privacy-preserving algorithms for various problems;
Integration of different privacy-preserving methods in applications;
Game-theoretic problems appearing in privacy-preserving applications.

The workshop solicits extended abstracts (up to three pages in the LNCS format, including the bibliography) of recent or ongoing work. There will be no formal proceedings, but the abstracts of accepted talks will be made available at the workshop. The presentation of recent work that has been published elsewhere is permitted. At least one author of each accepted abstract is required to register to the workshop and present the work.

The organizers of this workshop are planning an edited book on practical aspects of SMC. The authors of the submissions to the workshop may be solicited for chapters in this book.