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Guo, Jinyi, Ren, Wei, Ren, Yi 
ORCID: https://orcid.org/0000-0001-7423-6719 and Zhu, Tianqin
(2018)
A watermark-based in-situ access control model for image big data.
Future Internet, 10 (8).
ISSN 1999-5903
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Abstract
When large images are used for big data analysis, they impose new challenges in protecting image privacy. For example, a geographic image may consist of several sensitive areas or layers. When it is uploaded into servers, the image will be accessed by diverse subjects. Traditional access control methods regulate access privileges to a single image, and their access control strategies are stored in servers, which imposes two shortcomings: (1) fine-grained access control is not guaranteed for areas/layers in a single image that need to maintain secret for different roles; and (2) access control policies that are stored in servers suffers from multiple attacks (e.g., transferring attacks). In this paper, we propose a novel watermark-based access control model in which access control policies are associated with objects being accessed (called an in-situ model). The proposed model integrates access control policies as watermarks within images, without relying on the availability of servers or connecting networks. The access control for images is still maintained even though images are redistributed again to further subjects. Therefore, access control policies can be delivered together with the big data of images. Moreover, we propose a hierarchical key-role-area model for fine-grained encryption, especially for large size images such as geographic maps. The extensive analysis justifies the security and performance of the proposed model.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | access control,watermark,image,big data |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 31 Aug 2018 11:33 |
| Last Modified: | 23 Oct 2024 23:49 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/68174 |
| DOI: | 10.3390/fi10080069 |
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