Secure searching of biomarkers through hybrid homomorphic encryption schemeopen access
- Authors
- Kim, Miran; Song, Yongsoo; Cheon, Jung Hee
- Issue Date
- Jul-2017
- Publisher
- BMC
- Citation
- BMC MEDICAL GENOMICS, v.10, no.2
- Indexed
- SCIE
SCOPUS
- Journal Title
- BMC MEDICAL GENOMICS
- Volume
- 10
- Number
- 2
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/193054
- DOI
- 10.1186/s12920-017-0280-3
- ISSN
- 17558794
- Abstract
- Background: As genome sequencing technology develops rapidly, there has lately been an increasing need to keep genomic data secure even when stored in the cloud and still used for research. We are interested in designing a protocol for the secure outsourcing matching problem on encrypted data.,Method: We propose an efficient method to securely search a matching position with the query data and extract some information at the position. After decryption, only a small amount of comparisons with the query information should be performed in plaintext state. We apply this method to find a set of biomarkers in encrypted genomes. The important feature of our method is to encode a genomic database as a single element of polynomial ring.,Result: Since our method requires a single homomorphic multiplication of hybrid scheme for query computation, it has the advantage over the previous methods in parameter size, computation complexity, and communication cost. In particular, the extraction procedure not only prevents leakage of database information that has not been queried by user but also reduces the communication cost by half. We evaluate the performance of our method and verify that the computation on large-scale personal data can be securely and practically outsourced to a cloud environment during data analysis. It takes about 3.9 s to search-and-extract the reference and alternate sequences at the queried position in a database of size 4M.,Conclusion: Our solution for finding a set of biomarkers in DNA sequences shows the progress of cryptographic techniques in terms of their capability can support real-world genome data analysis in a cloud environment.,
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