%0 Conference Proceedings
%T Privacy-Preserving Elastic Net for Data Encrypted by Different Keys - With an Application on Biomarker Discovery
%+ The University of Hong Kong (HKU)
%+ The Chinese University of Hong Kong [Hong Kong] (CUHK)
%A Zhang, Jun
%A He, Meiqi
%A Yiu, Siu-Ming
%Z Part 2: Privacy
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 31th IFIP Annual Conference on Data and Applications Security and Privacy (DBSEC)
%C Philadelphia, PA, United States
%Y Giovanni Livraga
%Y Sencun Zhu
%I Springer International Publishing
%3 Data and Applications Security and Privacy XXXI
%V LNCS-10359
%P 185-204
%8 2017-07-19
%D 2017
%R 10.1007/978-3-319-61176-1_10
%K Privacy-preserving elastic net
%K Multiple encryption keys
%K Encrypted gene expression profiles
%K Biomarker discovery
%Z Computer Science [cs]Conference papers
%X Elastic net is a popular linear regression tool and has many important applications, in particular, finding genomic biomarkers for cancers from gene expression profiles for personalized medicine (elastic net is currently the most accurate prediction method for this problem). There is an increasing trend for organizations to store their data (e.g. gene expression profiles) in an untrusted third-party cloud system in order to leverage both its storage capacity and computational power. Due to the privacy concern, data must be stored in its encrypted form. While there are quite a number of privacy-preserving data mining protocols on encrypted data, there does not exist one for elastic net. In this paper, we propose the first privacy-preserving elastic net protocol using two non-colluding servers. Our protocol is able to handle expression profiles encrypted from multiple medical units using different encryption keys. Thus, collaboration between multiple medical units are made possible without jeopardizing the privacy of data records. We formally prove that our protocol is secure and implemented the protocol. The experimental results show that our protocol runs reasonably fast, thus can be applied in practice.
%G English
%Z TC 11
%Z WG 11.3
%2 https://inria.hal.science/hal-01684371v1/document
%2 https://inria.hal.science/hal-01684371v1/file/453481_1_En_10_Chapter.pdf
%L hal-01684371
%U https://inria.hal.science/hal-01684371
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC11
%~ IFIP-WG11-3
%~ IFIP-DBSEC
%~ IFIP-LNCS-10359