Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77055
Title: A selective privacy-preserving approach for multimedia data
Authors: Li, H
Wang, K
Liu, X 
Sun, Y
Guo, S 
Keywords: Big data
Cybercrime
Data analysis
Multimedia data
Privacy weights
Resource constraints
Security
Security levels
Time constraints
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE multimedia, 2017, v. 24, no. 4, 8100672, p. 14-25 How to cite?
Journal: IEEE multimedia 
Abstract: With the significant improvements in mobile digital devices and wireless networking technologies, we have witnessed the explosion of multimedia data. Because it is dynamic, vast in volume, and heterogeneous, this data not only evokes various novel data-driven services and applications, but also brings considerable security threats. In this article, the authors focus on privacy leakage issues in multimedia systems and study how to maximize the total privacy weights and upgrade the security level given predefined time and resource constraints. To this end, they propose a selective privacy-preserving method that adaptively allocates encryption resources according to the privacy weight and execution time of each data package. That is, it selects the encryption method with the appropriate complexity and security level for each multimedia data package. It first divides the data randomly into two parts, then performs XOR operations and generates cipher keys in different cloud storages to prevent users' original information from being attacked by untrusted cloud operators. Extensive simulation results have demonstrated the advantages and superiority of the proposed method over previous schemes. This article is part of a special issue on cybersecurity.
URI: http://hdl.handle.net/10397/77055
ISSN: 1070-986X
EISSN: 1941-0166
DOI: 10.1109/MMUL.2017.4031322
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