Secure searching of biomarkers through hybrid homomorphic encryption scheme

Abstract

BackgroundAs 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.MethodWe 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.ResultSince 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.ConclusionOur 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.

FPGA-Based Hardware Accelerator for Leveled Ring-LWE Fully Homomorphic Encryption

“…KeySwitch includes the generation of switching key and switching key two functional parts. Generally, the former one is generated by the software in the key generation step, it takes an extended key (initially we have pk ) and produces another extended key by adding in a so-called "key-switching matrix" from the 2 ' s to ' s , to return a new extended key epk (i.e. switching key KeySwitch is another most computationally intensive operation in BGV scheme.…”

“…Because FHE has the property that any computation on ciphertext is equivalent to performing the same computation on plaintext, the users can obtain the final result by decrypting the ciphertext with private keys. Some interesting applications of FHE include: secure outsourcing matching computation on genomic data [2], private information retrieval (PIR) and privacy-preserving data mining (PPDM) [3], multi-party computation (MPC) and privacy-preserving prediction from consumption data in smart electronic instrumentation [4], training neural networks over encrypted data [5,6] etc.…”

A systematic review on the status and progress of homomorphic encryption technologies

“…The studies that focused on the application of homomorphic encryption in health care systems include Tang et al [67], Çetin et al [68], Emmanuel et al [22], [23], Bocu and Costache [69], and Wang and Zhang [70]. Some other applications include encryption of biomarkers and other genetic data, especially given that the medical fraternity is moving towards personalized health [71,72,18,73,74]. The studies explored the application of encryption in ensuring privacy and protection of patient data amid concerns regarding the probably misuse of information electronic medical records and other healthcare database systems.…”

Secure Testing for Genetic Diseases on Encrypted Genomes with Homomorphic Encryption Scheme

“…The contributions of this paper focus on optimizing the design and improving the correctness of the scheme. Through the analysis of the [21] and its related code, we found three types of query errors in [KSC17], called losing of partial coefficient error (LPCE), hash collision error (HCE), and coefficient combination error (CCE), and made some improvements as follows.…”

“…For the challenge published by iDASH, Kim et al give a practical solution called [KSC17], which uses the homomorphic encryption technique to encrypt the entire gene database as a polynomial on the ring, thus solving the challenge of testing genetic disease (security outsourcing) to a certain extent [21].…”