Cloud-Based Quadratic Optimization With Partially Homomorphic Encryption

Andreea B. Alexandru, Konstantinos Gatsis, Yasser Shoukry, Sanjit A. Seshia, Paulo Tabuada, and George J. Pappas. Cloud-Based Quadratic Optimization With Partially Homomorphic Encryption. IEEE Transactions on Automatic Control, 66(5):2357–2364, 2021.

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Abstract

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

BibTeX

@article{alexandru-tac21,
  author    = {Andreea B. Alexandru and
               Konstantinos Gatsis and
               Yasser Shoukry and
               Sanjit A. Seshia and
               Paulo Tabuada and
               George J. Pappas},
  title     = {Cloud-Based Quadratic Optimization With Partially Homomorphic Encryption},
  journal   = {{IEEE} Transactions on Automatic Control},
  volume    = {66},
  number    = {5},
  pages     = {2357--2364},
  year      = {2021},
  abstract  = {This article develops a cloud-based protocol for a constrained quadratic optimization problem involving multiple parties, each holding private data. The protocol is based on the projected gradient ascent on the Lagrange dual problem and exploits partially homomorphic encryption and secure communication techniques. Using formal cryptographic definitions of indistinguishability, the protocol is shown to achieve computational privacy. We show the implementation results of the protocol and discuss its computational and communication complexity. We conclude this article with a discussion on privacy notions.},
}