A selective privacy-preserving approach for multimedia data

Huining Li, Kun Wang, Xiulong Liu, Yanfei Sun, Song Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

19 Citations (Scopus)

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.

Original languageEnglish
Article number8100672
Pages (from-to)14-25
Number of pages12
JournalIEEE Multimedia
Volume24
Issue number4
DOIs
Publication statusPublished - 1 Oct 2017

Keywords

  • big data
  • cybercrime
  • data analysis
  • multimedia data
  • privacy weights
  • resource constraints
  • security
  • security levels
  • time constraints

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Media Technology
  • Hardware and Architecture
  • Computer Science Applications

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