The success of data analytics relies on the availability of high quality data and effective information sharing. Yet, collected data often contain sensitive information about individuals, and sharing such data could potentially violate individual privacy. The current privacy protection practice primarily relies on policies and guidelines to restrict the types of publishable data, and agreements on the use and storage of sensitive data. The limitation of this approach is that it can be overly restrictive, and contracts and agreements cannot guarantee that sensitive information will not be carelessly misplaced and end up in the wrong hands. The goal of this research track is to provide a platform for knowledge exchange between theoreticians and practitioners in the areas of privacy protection, information security, and cloud computing.