Homomorphic-Encrypted Volume Rendering

Sebastian Mazza, Daniel Patel, Ivan Viola
Homomorphic-Encrypted Volume Rendering
IEEE Transactions on Visualization andComputer Graphics, 27:1-10, October 2020. [image] [Paper]

Information

  • Publication Type: Journal Paper with Conference Talk
  • Workgroup(s)/Project(s):
  • Date: October 2020
  • Call for Papers: Call for Paper
  • Date (from): 10. January 2020
  • Date (to): 13. October 2020
  • DOI: 10.1109/TVCG.2020.3030436
  • Event: IEEE VIS (SciVis) 2020 conference
  • Journal: IEEE Transactions on Visualization andComputer Graphics
  • Lecturer: Sebastian Mazza
  • Open Access: yes
  • Pages (from): 1
  • Pages (to): 10
  • Volume: 27
  • Keywords: Volume Rendering, Transfer Function, Homomorphic-Encryption, Paillier

Abstract

Computationally demanding tasks are typically calculated in dedicated data centers, and real-time visualizations also follow this trend. Some rendering tasks, however, require the highest level of confidentiality so that no other party, besides the owner, can read or see the sensitive data. Here we present a direct volume rendering approach that performs volume rendering directly on encrypted volume data by using the homomorphic Paillier encryption algorithm. This approach ensures that the volume data by using the homomorphic Paillier encryption algorithm. This approach ensures that the volume data and rendered image are uninterpretable to the rendering server. Our volume rendering pipeline introduces novel approaches for encrypted-data compositing, interpolation, and opacity modulation, as well as simple transfer function design, where each of these routines maintains the highest level of privacy. We present performance and memory overhead analysis that is associated with our privacy-preserving scheme. Our approach is open and secure by design, as opposed to secure through obscurity. Owners of the data only have to keep their secure key confidential to guarantee the privacy of their volume data and the rendered images. Our work is, to our knowledge, the first privacy-preserving remote volume-rendering approach that does not require that any server involved be trustworthy; even in cases when the server is compromised, no sensitive data will be leaked to a foreign party.

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BibTeX

@article{Mazza_2020,
  title =      "Homomorphic-Encrypted Volume Rendering",
  author =     "Sebastian Mazza and Daniel Patel and Ivan Viola",
  year =       "2020",
  abstract =   "Computationally demanding tasks are typically calculated in
               dedicated data centers, and real-time visualizations also
               follow this trend. Some rendering tasks, however, require
               the highest level of confidentiality so that no other party,
               besides the owner, can read or see the sensitive data. Here
               we present a direct volume rendering approach that performs
               volume rendering directly on encrypted volume data by using
               the homomorphic Paillier encryption algorithm. This approach
               ensures that the volume data by using the homomorphic
               Paillier encryption algorithm. This approach ensures that
               the volume data and rendered image are uninterpretable to
               the rendering server. Our volume rendering pipeline
               introduces novel approaches for encrypted-data compositing,
               interpolation, and opacity modulation, as well as simple
               transfer function design, where each of these routines
               maintains the highest level of privacy. We present
               performance and memory overhead analysis that is associated
               with our privacy-preserving scheme. Our approach is open and
               secure by design, as opposed to secure through obscurity.
               Owners of the data only have to keep their secure key
               confidential to guarantee the privacy of their volume data
               and the rendered images. Our work is, to our knowledge, the
               first privacy-preserving remote volume-rendering approach
               that does not require that any server involved be
               trustworthy; even in cases when the server is compromised,
               no sensitive data will be leaked to a foreign party.",
  month =      oct,
  doi =        "10.1109/TVCG.2020.3030436",
  journal =    "IEEE Transactions on Visualization andComputer Graphics",
  volume =     "27",
  pages =      "1--10",
  keywords =   "Volume Rendering, Transfer Function, Homomorphic-Encryption,
               Paillier",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/",
}