TY - JOUR
T1 - Homomorphic-Encrypted Volume Rendering
AU - Mazza, Sebastian
AU - Patel, Daniel
AU - Viola, Ivan
N1 - KAUST Repository Item: Exported on 2020-10-15
Acknowledged KAUST grant number(s): BAS/1/1680-01-01
Acknowledgements: The authors wish to thank Michal Hojsk for his fruitful discussions on cryptography. The authors would like to thank Michael Cusack from
Publication Services at KAUST for proofreading. The research was supported by King Abdullah University of Science and Technology
(KAUST) under award number BAS/1/1680-01-01.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/665573
UR - https://ieeexplore.ieee.org/document/9222562/
U2 - 10.1109/TVCG.2020.3030436
DO - 10.1109/TVCG.2020.3030436
M3 - Article
C2 - 33048733
SN - 2160-9306
SP - 1
EP - 1
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
ER -