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Multiparty Computation: To Secure Privacy, Do the Math: A discussion with Nigel Smart, Joshua W. Baron, Sanjay Saravanan, Jordan Brandt, and Atefeh Mashatan

Summary

Multiparty Computation is based on complex math, and over the past decade, MPC has been harnessed as one of the most powerful tools available for the protection of sensitive data. MPC now serves as the basis for protocols that let a set of parties interact and compute on a pool of private inputs without revealing any of the data contained within those inputs. In the end, only the results are revealed. The implications of this can often prove profound.

Keywords

Security and privacy, Cryptography, Theory of computation, Computational complexity and cryptography, Social and professional topics

2021 Journal Impact Factor: N/A

Publication date:  December 2023

Links

References

APA Smart, N., Baron, J. W., Saravanan, S., Brandt, J., & Mashatan, A. (2023). Multiparty computation: To secure privacy, do the math. Queue21(6), 78–100.
BibTeX @article{10.1145/3639448,
author = {Smart, Nigel and Baron, Joshua W. and Saravanan, Sanjay and Brandt, Jordan and Mashatan, Atefeh},
title = {Multiparty Computation: To Secure Privacy, Do the Math: A discussion with Nigel Smart, Joshua W. Baron, Sanjay Saravanan, Jordan Brandt, and Atefeh Mashatan},
year = {2024},
issue_date = {November/December 2023},
publisher = {Association for Computing Machinery},
volume = {21},
number = {6},
url = {https://doi.org/10.1145/3639448},
journal = {Queue},
pages = {78–100}
}
DOI https://doi.org/10.1145/3639448
IEEE N. Smart, J. W. Baron, S. Saravanan, J. Brandt, and A. Mashatan, “Multiparty Computation: To Secure Privacy, Do the Math: A discussion with Nigel Smart, Joshua W. Baron, Sanjay Saravanan, Jordan Brandt, and Atefeh Mashatan,” Queue, vol. 21, no. 6, pp. 78–100, Dec. 2023. doi: 10.1145/3639448.
ISSN 1542-7730