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Article: Privacy-preserving edge-assisted image retrieval and classification in IoT

TitlePrivacy-preserving edge-assisted image retrieval and classification in IoT
Authors
KeywordsInternet of Things
outsourced computation
privacy protection
cryptographic primitive
image processing
Issue Date2019
PublisherSpringer Verlag. The Journal's web site is located at http://journal.hep.com.cn/fcs/EN/2095-2228/current.shtml
Citation
Frontiers of Computer Science, 2019, v. 13, p. 1136-1147 How to Cite?
AbstractInternet of Things (IoT) has drawn much attention in recent years. However, the image data captured by IoT terminal devices are closely related to users’ personal information, which are sensitive and should be protected. Though traditional privacy-preserving outsourced computing solutions such as homomorphic cryptographic primitives can support privacy-preserving computing, they consume a significant amount of computation and storage resources. Thus, it becomes a heavy burden on IoT terminal devices with limited resources. In order to reduce the resource consumption of terminal device, we propose an edge-assisted privacy-preserving outsourced computing framework for image processing, including image retrieval and classification. The edge nodes cooperate with the terminal device to protect data and support privacy-preserving computing on the semi-trusted cloud server. Under this framework, edge-assisted privacy-preserving image retrieval and classification schemes are proposed in this paper. The security analysis and performance evaluation show that the proposed schemes greatly reduce the computational, communication and storage burden of IoT terminal device while ensuring image data security.
Persistent Identifierhttp://hdl.handle.net/10722/277567
ISSN
2019 Impact Factor: 1.275
2015 SCImago Journal Rankings: 0.369

 

DC FieldValueLanguage
dc.contributor.authorLi, X-
dc.contributor.authorLi, J-
dc.contributor.authorYiu, S-
dc.contributor.authorGao, C-
dc.contributor.authorXiong, J-
dc.date.accessioned2019-09-20T08:53:31Z-
dc.date.available2019-09-20T08:53:31Z-
dc.date.issued2019-
dc.identifier.citationFrontiers of Computer Science, 2019, v. 13, p. 1136-1147-
dc.identifier.issn2095-2228-
dc.identifier.urihttp://hdl.handle.net/10722/277567-
dc.description.abstractInternet of Things (IoT) has drawn much attention in recent years. However, the image data captured by IoT terminal devices are closely related to users’ personal information, which are sensitive and should be protected. Though traditional privacy-preserving outsourced computing solutions such as homomorphic cryptographic primitives can support privacy-preserving computing, they consume a significant amount of computation and storage resources. Thus, it becomes a heavy burden on IoT terminal devices with limited resources. In order to reduce the resource consumption of terminal device, we propose an edge-assisted privacy-preserving outsourced computing framework for image processing, including image retrieval and classification. The edge nodes cooperate with the terminal device to protect data and support privacy-preserving computing on the semi-trusted cloud server. Under this framework, edge-assisted privacy-preserving image retrieval and classification schemes are proposed in this paper. The security analysis and performance evaluation show that the proposed schemes greatly reduce the computational, communication and storage burden of IoT terminal device while ensuring image data security.-
dc.languageeng-
dc.publisherSpringer Verlag. The Journal's web site is located at http://journal.hep.com.cn/fcs/EN/2095-2228/current.shtml-
dc.relation.ispartofFrontiers of Computer Science-
dc.rightsThis is a post-peer-review, pre-copyedit version of an article published in [insert journal title]. The final authenticated version is available online at: http://dx.doi.org/[insert DOI]-
dc.subjectInternet of Things-
dc.subjectoutsourced computation-
dc.subjectprivacy protection-
dc.subjectcryptographic primitive-
dc.subjectimage processing-
dc.titlePrivacy-preserving edge-assisted image retrieval and classification in IoT-
dc.typeArticle-
dc.identifier.emailYiu, S: smyiu@cs.hku.hk-
dc.identifier.authorityYiu, S=rp00207-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s11704-018-8067-z-
dc.identifier.scopuseid_2-s2.0-85060615606-
dc.identifier.hkuros305928-
dc.identifier.volume13-
dc.identifier.spage1136-
dc.identifier.epage1147-
dc.publisher.placeGermany-

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