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Hiding Media Data Via Shaders: Enabling Private Sharing in the Clouds
The 8th IEEE International Conference on Cloud Computing (CLOUD) (2015)
  • Kaikai Liu, University of Florida
  • Min Li, University of Florida
  • Xiaolin Li, University of Florida
Abstract
In the era of Cloud and Social Networks, mobile devices exhibit much more powerful abilities for big media data storage and sharing. However, many users are still reluctant to share/store their data via clouds due to the potential leakage of confidential or private information. Although some cloud services provide storage encryption and access protection, privacy risks are still high since the protection is not always adequately conducted from end-to-end. Most customers are aware of the danger of letting data control out of their hands, e.g., Storing them to YouTube, Flickr, Facebook, Google+. Because of substantial practical and business needs, existing cloud services are restricted to the desired formats, e.g., Video and photo, without allowing arbitrary encrypted data. In this paper, we propose a format-compliant end-to-end privacy-preserving scheme for media sharing/storage issues with considerations for big data, clouds, and mobility. To realize efficient encryption for big media data, we jointly achieve format-compliant, compression-independent and correlation-preserving via multi-channel chained solutions under the guideline of Markov cipher. The encryption and decryption process is integrated into an image/video filter via GPU Shader for display-to-display full encryption. The proposed scheme makes big media data sharing/storage safer and easier in the clouds.
Keywords
  • Privacy,
  • Cloud,
  • Media Data,
  • Encryption,
  • Format-Compliant,
  • Chaotic Mapping
Publication Date
June, 2015
DOI
10.1109/CLOUD.2015.26
Publisher Statement
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Citation Information
Kaikai Liu, Min Li and Xiaolin Li. "Hiding Media Data Via Shaders: Enabling Private Sharing in the Clouds" The 8th IEEE International Conference on Cloud Computing (CLOUD) (2015) p. 122 - 129
Available at: http://works.bepress.com/kaikai-liu/1/