Cloud-Based Quadratic Optimization With Partially Homomorphic Encryption

نویسندگان

چکیده

This article develops a cloud-based protocol for constrained quadratic optimization problem involving multiple parties, each holding private data. The is based on the projected gradient ascent Lagrange dual and exploits partially homomorphic encryption secure communication techniques. Using formal cryptographic definitions of indistinguishability, shown to achieve computational privacy. We show implementation results discuss its complexity. conclude this with discussion privacy notions.

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ژورنال

عنوان ژورنال: IEEE Transactions on Automatic Control

سال: 2021

ISSN: ['0018-9286', '1558-2523', '2334-3303']

DOI: https://doi.org/10.1109/tac.2020.3005920