Secure approximation of edit distance on genomic data

The authors ‘propose two different approximation methods to securely compute the edit distance among genomic sequences. [They] use shingling, private set intersection methods, the banded alignment algorithm, and garbled circuits to implement these methods.’

  • Al Aziz MM, Alhadidi D, Mohammed N
    Secure approximation of edit distance on genomic data
    BMC Medical Genomics 2017 10(Suppl 2):41
    (Abstract, PDF, Source Code)

Efficient and secure outsourcing of genomic data storage

The authors ‘present a novel privacy-preserving algorithm for fully outsourcing the storage of large genomic data files to a public cloud and enabling researchers to efficiently search for variants of interest. In order to protect data and query confidentiality from possible leakage, [their] solution exploits optimal encoding for genomic variants and combines it with homomorphic encryption and private information retrieval.’

  • Sousa JS, Lefebvre C, Huang Z, Raisaro JL, Aguilar-Melchor C, Killijian MO, Hubaux JP
    Efficient and secure outsourcing of genomic data storage
    BMC Medical Genomics 2017 10(Suppl 2):46
    (Abstract, PDF, Source Code)

Aftermath of bustamante attack on genomic beacon service

The authors ‘propose two lightweight algorithms (based on randomized response) which captures the efficacy while preserving the privacy of the participants in a genomic beacon service. [They] also elaborate the strength and weakness of the attack by explaining some of their statistical and mathematical models using real world genomic database.’

  • Al Aziz MM, Ghasemi R, Waliullah M, Mohammed N
    Aftermath of bustamante attack on genomic beacon service
    BMC Medical Genomics 2017 10(Suppl 2):43
    (Abstract, PDF, Source Code)

Bloom filter based oblivious outsourced matchings

The authors ‘propose Fhe-Bloom and Phe-Bloom, two efficient approaches for genetic disease testing using homomorphically encrypted Bloom filters. Both approaches allow the data owner to securely outsource storage and computation to an untrusted cloud. Fhe-Bloom is fully secure in the semi-honest model while Phe-Bloom slightly relaxes security guarantees in a trade-off for highly improved performance.’

  • Ziegeldorf JH, Pennekamp J, Hellmanns D, Schwinger F, Kunze I, Henze M, Hiller J, Matzutt R, Wehrle K
    BLOOM: BLoom filter based oblivious outsourced matchings
    BMC Medical Genomics 2017 10(Suppl 2):44
    (Abstract, PDF, Source Code)

Privacy-preserving genetic testing via Software Guard Extension

The authors ‘present one of the first implementations of Software Guard Extension (SGX) based securely outsourced genetic testing framework, which leverages multiple cryptographic protocols and minimal perfect hash scheme to enable efficient and secure data storage and computation outsourcing.’

  • Chen F, Wang C, Dai W, Jiang X, Mohammed N, Al Aziz MM, Sadat MN, Sahinalp C, Lauter K, Wang S
    PRESAGE: PRivacy-preserving gEnetic testing via SoftwAre Guard Extension
    BMC Medical Genomics 2017 10(Suppl 2):48
    (Abstract, PDF)

Private queries on encrypted genomic data

Çetin et al. present ‘a novel string matching protocol to enable privacy-preserving queries on homomorphically encrypted data. [Their] protocol combines state-of-the-art techniques from homomorphic encryption and private set intersection protocols to minimize the computational and communication cost.’

  • Çetin GS, Chen H, Laine K, Lauter K, Rindal P, Xia Y
    Private queries on encrypted genomic data
    BMC Medical Genomics 2017 10(Suppl 2):45
    (Abstract, PDF)

Secure searching of biomarkers through hybrid homomorphic encryption scheme

The authors ‘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. [They] 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 [a] polynomial ring.’

  • Kim M, Song Y, Cheon JH
    Secure searching of biomarkers through hybrid homomorphic encryption scheme
    BMC Medical Genomics 2017 10(Suppl 2):42
    (Abstract, PDF)

Private genome analysis through homomorphic encryption

The authors ‘present evaluation algorithms for secure computation of the minor allele frequencies and chi square statistic in a genome-wide association studies setting. [They] also describe how to privately compute the Hamming distance and approximate Edit distance between encrypted DNA sequences. Finally, [they] compare performance details of using two practical homomorphic encryption schemes – the BGV scheme by Gentry, Halevi and Smart and the YASHE scheme by Bos, Lauter, Loftus and Naehrig.’

  • Kim M, Lauter K
    Private genome analysis through homomorphic encryption
    BMC Medical Informatics and Decision Making 2015 15(Suppl 5):S3
    (Abstract, PDF)

Privacy-preserving genome-wide association studies on cloud environment using fully homomorphic encryption

‘To maintain the privacy of subjects’, the authors ‘propose encryption of all genotype and phenotype data. To allow the cloud to perform meaningful computation in relation to the encrypted data, [they] use a fully homomorphic encryption scheme. Noting that [they] can evaluate typical statistics for GWAS from a frequency table, [their] solution evaluates frequency tables with encrypted genomic and clinical data as input. [They] propose to use a packing technique for efficient evaluation of these frequency tables.’

  • Lu WJ, Yamada Y, Sakuma J
    Privacy-preserving genome-wide association studies on cloud environment using fully homomorphic encryption
    BMC Medical Informatics and Decision Making 2015 15(Suppl 5):S1
    (Abstract, PDF)