Privacy-Preserving Elastic Net for Data Encrypted by Different Keys - With an Application on Biomarker Discovery - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

Privacy-Preserving Elastic Net for Data Encrypted by Different Keys - With an Application on Biomarker Discovery

Jun Zhang
  • Fonction : Auteur
  • PersonId : 1026650
Meiqi He
  • Fonction : Auteur
  • PersonId : 1026651

Résumé

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.
Fichier principal
Vignette du fichier
453481_1_En_10_Chapter.pdf (740.75 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01684371 , version 1 (15-01-2018)

Licence

Paternité

Identifiants

Citer

Jun Zhang, Meiqi He, Siu-Ming Yiu. Privacy-Preserving Elastic Net for Data Encrypted by Different Keys - With an Application on Biomarker Discovery. 31th IFIP Annual Conference on Data and Applications Security and Privacy (DBSEC), Jul 2017, Philadelphia, PA, United States. pp.185-204, ⟨10.1007/978-3-319-61176-1_10⟩. ⟨hal-01684371⟩
514 Consultations
79 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More