Preserving privacy in pre-classification volume ray-casting of 3D images

Mohanty, M; Asghar, MR; Russello, G

Preserving privacy in pre-classification volume ray-casting of 3D images

Mohanty, M

Asghar, MR Russello, G

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Publisher:: Institution of Engineering and Technology
Publication Type:: Chapter
Citation:: Data Security in Cloud Computing, 2017, pp. 45-64
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Mohanty, M https://orcid.org/0000-0002-0258-4586
dc.contributor.author	Asghar, MR
dc.contributor.author	Russello, G
dc.date.accessioned	2022-12-14T02:32:15Z
dc.date.available	2022-12-14T02:32:15Z
dc.date.issued	2017-01-01
dc.identifier.citation	Data Security in Cloud Computing, 2017, pp. 45-64
dc.identifier.isbn	9781785612206
dc.identifier.uri	http://hdl.handle.net/10453/164395
dc.description.abstract	With the evolution of cloud computing, organizations are outsourcing the storage and rendering of volume (i.e., 3D data) to cloud servers. Data confidentiality at the thirdparty cloud provider, however, is one of the main challenges. Although state-of-the-art non-homomorphic encryption schemes can protect confidentiality by encrypting the volume, they do not allowrendering operations on the encrypted volumes. In this chapter, we address this challenge by proposing 3DCrypt-a modified Paillier cryptosystem scheme for multiuser settings that allows cloud datacenters to render the encrypted volume. The rendering technique we consider in this work is the pre-classification volume ray-casting. 3DCrypt is such that multiple users can render volumes without sharing any encryption keys. 3DCrypt’s storage and computational overheads are approximately 66.3 MB and 27 s, respectively, when rendering is performed on a 256 × 256 × 256 volume for a 256 × 256 image space. We have also proved that 3DCrypt is INDistinguishable under Chosen Plaintext Attack (IND-CPA) secure.
dc.language	en
dc.publisher	Institution of Engineering and Technology
dc.relation.ispartof	Data Security in Cloud Computing
dc.relation.isbasedon	10.1049/PBSE007E_ch3
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Preserving privacy in pre-classification volume ray-casting of 3D images
dc.type	Chapter
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CFS - Centre for Forensic Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access	*
dc.date.updated	2022-12-14T02:32:11Z
pubs.publication-status	Published

Abstract:

With the evolution of cloud computing, organizations are outsourcing the storage and rendering of volume (i.e., 3D data) to cloud servers. Data confidentiality at the thirdparty cloud provider, however, is one of the main challenges. Although state-of-the-art non-homomorphic encryption schemes can protect confidentiality by encrypting the volume, they do not allowrendering operations on the encrypted volumes. In this chapter, we address this challenge by proposing 3DCrypt-a modified Paillier cryptosystem scheme for multiuser settings that allows cloud datacenters to render the encrypted volume. The rendering technique we consider in this work is the pre-classification volume ray-casting. 3DCrypt is such that multiple users can render volumes without sharing any encryption keys. 3DCrypt’s storage and computational overheads are approximately 66.3 MB and 27 s, respectively, when rendering is performed on a 256 × 256 × 256 volume for a 256 × 256 image space. We have also proved that 3DCrypt is INDistinguishable under Chosen Plaintext Attack (IND-CPA) secure.

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http://hdl.handle.net/10453/164395