Visible to the public Privacy-safe linkage analysis with homomorphic encryption

TitlePrivacy-safe linkage analysis with homomorphic encryption
Publication TypeConference Paper
Year of Publication2017
AuthorsUgwuoke, C., Erkin, Z., Lagendijk, R. L.
Conference Name2017 25th European Signal Processing Conference (EUSIPCO)
Keywordsallele-allele, association analysis, Bioinformatics, biologically coded information, biology computing, contingency table, cryptography, data privacy, disease, diseases, encrypted domain, Encryption, gene phenotypes, genetic data, genetic epidemiology, genetic locus, Genetics, genome analyses algorithms, genome data, genome data privacy, genomic data, genomics, homomorphic encryption, homomorphic encryption schemes, human factors, human genome, linkage disequilibrium measures, Metrics, patient response, personalised medicine, privacy-safe linkage analysis, pubcrawl, Resiliency, Scalability

Genetic data are important dataset utilised in genetic epidemiology to investigate biologically coded information within the human genome. Enormous research has been delved into in recent years in order to fully sequence and understand the genome. Personalised medicine, patient response to treatments and relationships between specific genes and certain characteristics such as phenotypes and diseases, are positive impacts of studying the genome, just to mention a few. The sensitivity, longevity and non-modifiable nature of genetic data make it even more interesting, consequently, the security and privacy for the storage and processing of genomic data beg for attention. A common activity carried out by geneticists is the association analysis between allele-allele, or even a genetic locus and a disease. We demonstrate the use of cryptographic techniques such as homomorphic encryption schemes and multiparty computations, how such analysis can be carried out in a privacy friendly manner. We compute a 3 x 3 contingency table, and then, genome analyses algorithms such as linkage disequilibrium (LD) measures, all on the encrypted domain. Our computation guarantees privacy of the genome data under our security settings, and provides up to 98.4% improvement, compared to an existing solution.

Citation Keyugwuoke_privacy-safe_2017