  Searchable symmetric encryption (SSE) has been used to protect the
confidentiality of genomic data while providing substring search and range
queries on a sequence of genomic data, but it has not been studied for
protecting single nucleotide polymorphism (SNP)-phenotype data. In this
article, we propose a novel model, PrivGenDB, for securely storing and
efficiently conducting different queries on genomic data outsourced to an
honest-but-curious cloud server. To instantiate PrivGenDB, we use SSE to ensure
confidentiality while conducting different types of queries on encrypted
genomic data, phenotype and other information of individuals to help
analysts/clinicians in their analysis/care. To the best of our knowledge,
PrivGenDB construction is the first SSE-based approach ensuring the
confidentiality of shared SNP-phenotype data through encryption while making
the computation/query process efficient and scalable for biomedical research
and care. Furthermore, it supports a variety of query types on genomic data,
including count queries, Boolean queries, and k'-out-of-k match queries.
Finally, the PrivGenDB model handles the dataset containing both genotype and
phenotype, and it also supports storing and managing other metadata like gender
and ethnicity privately. Computer evaluations on a dataset with 5,000 records
and 1,000 SNPs demonstrate that a count/Boolean query and a k'-out-of-k match
query over 40 SNPs take approximately 4.3s and 86.4{\mu}s, respectively, that
outperforms the existing schemes.
