Towards Secure and Fast Mapping of Genomic Sequences on Public Clouds

The rapid advances in genomic technologies have led to the exponential growth of genomic data. On one hand, clinics and research institutions need to consider the security issue since the data privacy needs to be protected. On the other hand, they look for the means to improve the scalability and performance of genomic applications to be able to handle large amount of data as well as heavy computations. While existing approaches have to sacrifice one for the other, we aim at achieving all the three goals above. In this paper, we design an entire secure framework for genomic data processing on public clouds. Based on this framework, we propose a 3-encryption-scheme model for genomic sequence mapping (3EGSM), an important phase of genomic computation. The model protects not only genomic sequences but also the intermediate and final computation results when processing on public clouds. We evaluate the proposed framework through intensive experiments using real genomic data. The experimental results show that the proposed framework reduces the sequential mapping time by up to 75% compared to a baseline approach that considers only the security issue. The experimental results also show that the framework achieves high speedup when performing parallel processing.