Show simple item record

dc.contributor.authorHuang, Z.en_US
dc.contributor.authorAyday, Ermanen_US
dc.contributor.authorFellay, Jacquesen_US
dc.contributor.authorHubaux, J-P.en_US
dc.contributor.authorJuels, A.en_US
dc.date.accessioned2016-02-08T12:24:27Z
dc.date.available2016-02-08T12:24:27Z
dc.date.issued2015-05en_US
dc.identifier.urihttp://hdl.handle.net/11693/28585
dc.descriptionConference name: IEEE Symposium on Security and Privacy, 2015
dc.descriptionDate of Conference: 17-21 May 2015
dc.description.abstractSecure storage of genomic data is of great and increasing importance. The scientific community's improving ability to interpret individuals' genetic materials and the growing size of genetic database populations have been aggravating the potential consequences of data breaches. The prevalent use of passwords to generate encryption keys thus poses an especially serious problem when applied to genetic data. Weak passwords can jeopardize genetic data in the short term, but given the multi-decade lifespan of genetic data, even the use of strong passwords with conventional encryption can lead to compromise. We present a tool, called Geno Guard, for providing strong protection for genomic data both today and in the long term. Geno Guard incorporates a new theoretical framework for encryption called honey encryption (HE): it can provide information-theoretic confidentiality guarantees for encrypted data. Previously proposed HE schemes, however, can be applied to messages from, unfortunately, a very restricted set of probability distributions. Therefore, Geno Guard addresses the open problem of applying HE techniques to the highly non-uniform probability distributions that characterize sequences of genetic data. In Geno Guard, a potential adversary can attempt exhaustively to guess keys or passwords and decrypt via a brute-force attack. We prove that decryption under any key will yield a plausible genome sequence, and that Geno Guard offers an information-theoretic security guarantee against message-recovery attacks. We also explore attacks that use side information. Finally, we present an efficient and parallelized software implementation of Geno Guard. © 2015 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.titleProceedings - IEEE Symposium on Security and Privacy, 2015en_US
dc.relation.isversionofhttps://doi.org/10.1109/SP.2015.34en_US
dc.subjectBrute-force attacken_US
dc.subjectDistribution-transforming encoderen_US
dc.subjectGenomic privacyen_US
dc.subjectHoney encryptionen_US
dc.subjectAuthenticationen_US
dc.subjectCryptographyen_US
dc.subjectDigital storageen_US
dc.subjectFood productsen_US
dc.subjectGenesen_US
dc.subjectInformation theoryen_US
dc.subjectPopulation statisticsen_US
dc.subjectBrute-force attacken_US
dc.subjectDistribution-transforming encoderen_US
dc.subjectGenetic materialsen_US
dc.subjectGenome sequencesen_US
dc.subjectInformation- theoretic securitiesen_US
dc.subjectScientific communityen_US
dc.subjectSoftware implementationen_US
dc.subjectTheoretical frameworken_US
dc.subjectProbability distributionsen_US
dc.titleGenoGuard: protecting genomic data against brute-force attacksen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage447en_US
dc.citation.epage462en_US
dc.identifier.doi10.1109/SP.2015.34en_US
dc.publisherIEEE


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record