Multimedia Tools and Applications

, Volume 78, Issue 3, pp 3747–3765 | Cite as

A differential privacy noise dynamic allocation algorithm for big multimedia data

  • Guoqiang ZhouEmail author
  • Shui Qin
  • Hongfei Zhou
  • Dansong Cheng


An advanced differential privacy algorithm is proposed in this paper to solve the problem of non-uniformity faced with two-dimensional big multimedia data, such as images. Traditional privacy-preserving algorithms partition a spatial data space into grids and then add noise to each grid at same scale. Such a treatment increases relative errors and reduces accuracy. To address this issue, a differential privacy noise dynamic allocation algorithm is proposed based on the standard deviation circle radius hereafter referred to as SDC-DP algorithm. In our proposed algorithm, the intensity of privacy-preserving needs is defined by the divergence of each grid which is calculated by the standard deviation circle radius. The different scale of noise is mixed dynamically into count query results for each grid on the privacy-preserving needs. Experimental results show that the SDC-DP can effectively reduce the relative errors and improve accuracies, compared to the state-of-the-art techniques.


Big multimedia data Differential privacy SDC-DP Standard deviation circle radius Relative errors 



This work is supported by Shenzhen Science and Technology Innovation Commission (SZSTI) project No. JCYJ20170302153752613.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Guoqiang Zhou
    • 1
    Email author
  • Shui Qin
    • 1
  • Hongfei Zhou
    • 1
  • Dansong Cheng
    • 2
  1. 1.College of Computer ScienceNanjing University of Posts and TelecommunicationNanjingPeople’s Republic of China
  2. 2.School of computer scienceHarbin Institute of TechnologyHarbinPeople’s Republic of China

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