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dc.contributor.author
Backes, Michael
dc.contributor.author
Barbosa, Manuel
dc.contributor.author
Fiore, Dario
dc.contributor.author
Reischuk, Raphael M.
dc.date.accessioned
2020-10-02T07:31:40Z
dc.date.available
2017-06-11T18:23:59Z
dc.date.available
2020-10-02T07:31:40Z
dc.date.issued
2015
dc.identifier.isbn
978-1-4673-6949-7
en_US
dc.identifier.other
10.1109/SP.2015.24
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/102573
dc.description.abstract
We study the problem of privacy-preserving proofs on authenticated data, where a party receives data from a trusted source and is requested to prove computations over the data to third parties in a correct and private way, i.e., The third party learns no information on the data but is still assured that the claimed proof is valid. Our work particularly focuses on the challenging requirement that the third party should be able to verify the validity with respect to the specific data authenticated by the source -- even without having access to that source. This problem is motivated by various scenarios emerging from several application areas such as wearable computing, smart metering, or general business-to-business interactions. Furthermore, these applications also demand any meaningful solution to satisfy additional properties related to usability and scalability. In this paper, we formalize the above three-party model, discuss concrete application scenarios, and then we design, build, and evaluate ADSNARK, a nearly practical system for proving arbitrary computations over authenticated data in a privacy-preserving manner. ADSNARK improves significantly over state-of-the-art solutions for this model. For instance, compared to corresponding solutions based on Pinocchio (Oakland'13), ADSNARK achieves up to 25x improvement in proof-computation time and a 20x reduction in prover storage space.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.subject
Authentication
en_US
dc.subject
Privacy
en_US
dc.subject
Privacy-preserving proofs
en_US
dc.title
ADSNARK: Nearly practical and privacy-preserving proofs on authenticated data
en_US
dc.type
Conference Paper
dc.date.published
2015-07-20
ethz.book.title
2015 IEEE Symposium on Security and Privacy (SP 2015)
en_US
ethz.pages.start
271
en_US
ethz.pages.end
286
en_US
ethz.event
36th IEEE Symposium on Security and Privacy (SP 2015)
en_US
ethz.event.location
San Jose, CA, USA
en_US
ethz.event.date
May 17-21, 2015
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02660 - Institut für Informationssicherheit / Institute of Information Security::03975 - Perrig, Adrian / Perrig, Adrian
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02660 - Institut für Informationssicherheit / Institute of Information Security::03975 - Perrig, Adrian / Perrig, Adrian
ethz.date.deposited
2017-06-11T18:24:04Z
ethz.source
ECIT
ethz.identifier.importid
imp59365353a286699993
ethz.ecitpid
pub:160714
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2017-07-14T16:08:55Z
ethz.rosetta.lastUpdated
2022-03-29T03:16:08Z
ethz.rosetta.versionExported
true
ethz.COinS
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