The growth of genome data and computational requirements overwhelm the capacity of servers. Many institutions and NIH are considering the cloud computing service as a cost-effective alternative to scale up research. Privacy and security are the major concerns when deploying cloud-based data analysis tools. In the past few years, secure computation methods have witnessed significant performance improvement but it is still not clear if they are applicable to biomedical challenges involving big data. The goal of this challenge is to evaluate the performance of state-of-the-arts methods that ensures rigorous data confidentiality during data analysis in a cloud environment.