Homomorphically encrypted gradient descent algorithms for quadratic programming

In this paper, we evaluate the different fully homomorphic encryption schemes, propose an implementation, and numerically analyze the applicability of gradient descent algorithms to solve quadratic programming in a homomorphic encryption setup. The limit on the multiplication depth of homomorphic en...

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Main Authors: Bertolace, A, Gatsis, K, Margellos, K
Format: Conference item
Language:English
Published: IEEE 2024
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author Bertolace, A
Gatsis, K
Margellos, K
author_facet Bertolace, A
Gatsis, K
Margellos, K
author_sort Bertolace, A
collection OXFORD
description In this paper, we evaluate the different fully homomorphic encryption schemes, propose an implementation, and numerically analyze the applicability of gradient descent algorithms to solve quadratic programming in a homomorphic encryption setup. The limit on the multiplication depth of homomorphic encryption circuits is a major challenge for iterative procedures such as gradient descent algorithms. Our analysis not only quantifies these limitations on prototype examples, thus serving as a benchmark for future investigations, but also highlights additional trade-offs like the ones pertaining the choice of gradient descent or accelerated gradient descent methods, opening the road for the use of homomorphic encryption techniques in iterative procedures widely used in optimization based control. In addition, we argue that, among the available homomorphic encryption schemes, the one adopted in this work, namely CKKS, is the only suitable scheme for implementing gradient descent algorithms. The choice of the appropriate step size is crucial to the convergence of the procedure. The paper shows firsthand the feasibility of homomorphically encrypted gradient descent algorithms.
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spelling oxford-uuid:c257d82b-bc3d-41a7-ae3b-f1b34d66d05a2024-03-14T10:48:07ZHomomorphically encrypted gradient descent algorithms for quadratic programmingConference itemhttp://purl.org/coar/resource_type/c_5794uuid:c257d82b-bc3d-41a7-ae3b-f1b34d66d05aEnglishSymplectic ElementsIEEE2024Bertolace, AGatsis, KMargellos, KIn this paper, we evaluate the different fully homomorphic encryption schemes, propose an implementation, and numerically analyze the applicability of gradient descent algorithms to solve quadratic programming in a homomorphic encryption setup. The limit on the multiplication depth of homomorphic encryption circuits is a major challenge for iterative procedures such as gradient descent algorithms. Our analysis not only quantifies these limitations on prototype examples, thus serving as a benchmark for future investigations, but also highlights additional trade-offs like the ones pertaining the choice of gradient descent or accelerated gradient descent methods, opening the road for the use of homomorphic encryption techniques in iterative procedures widely used in optimization based control. In addition, we argue that, among the available homomorphic encryption schemes, the one adopted in this work, namely CKKS, is the only suitable scheme for implementing gradient descent algorithms. The choice of the appropriate step size is crucial to the convergence of the procedure. The paper shows firsthand the feasibility of homomorphically encrypted gradient descent algorithms.
spellingShingle Bertolace, A
Gatsis, K
Margellos, K
Homomorphically encrypted gradient descent algorithms for quadratic programming
title Homomorphically encrypted gradient descent algorithms for quadratic programming
title_full Homomorphically encrypted gradient descent algorithms for quadratic programming
title_fullStr Homomorphically encrypted gradient descent algorithms for quadratic programming
title_full_unstemmed Homomorphically encrypted gradient descent algorithms for quadratic programming
title_short Homomorphically encrypted gradient descent algorithms for quadratic programming
title_sort homomorphically encrypted gradient descent algorithms for quadratic programming
work_keys_str_mv AT bertolacea homomorphicallyencryptedgradientdescentalgorithmsforquadraticprogramming
AT gatsisk homomorphicallyencryptedgradientdescentalgorithmsforquadraticprogramming
AT margellosk homomorphicallyencryptedgradientdescentalgorithmsforquadraticprogramming