Privacy Preserving Fisher’s Exact Test on Genomic Data

Privacy of genomic data has become increasingly significant as genome sequencing is more readily available for research. It is imperative to protect genomic data as we use it for the progression of medicine. In this paper, we propose a new privacy preserving Fisher’s Exact Test algorithm for genomic data based on Boneh-Goh-Nissim (BGN) cryptosystem. This is a novel approach that has yet to be done to the best of our knowledge. Due to BGN’s homomorphic properties, researchers can keep data private while calculating the correct test results without ever decrypting the data itself. We investigate the usage of the BGN cryptosystem on statistical computations, Fisher’s Exact Test in particular, analyzing its security, efficiency, and correctness in the real world of genomic data research. We implement our BGN-based privacy preserving Fisher’s Exact Test algorithm and test it extensively using real genomic data from international genome database. The result shows that our algorithm is efficient and practical.