DeepAI AI Chat
Log In Sign Up

Cloud-based Quadratic Optimization with Partially Homomorphic Encryption

by   Andreea B. Alexandru, et al.

The development of large-scale distributed control systems has led to the outsourcing of costly computations to cloud-computing platforms, as well as to concerns about privacy of the collected sensitive data. This paper develops a cloud-based protocol for a quadratic optimization problem involving multiple parties, each holding information it seeks to maintain private. The protocol is based on the projected gradient ascent on the Lagrange dual problem and exploits partially homomorphic encryption and secure multi-party computation techniques. Using formal cryptographic definitions of indistinguishability, the protocol is shown to achieve computational privacy, i.e., there is no computationally efficient algorithm that any involved party can employ to obtain private information beyond what can be inferred from the party's inputs and outputs only. In order to reduce the communication complexity of the proposed protocol, we introduced a variant that achieves this objective at the expense of weaker privacy guarantees. We discuss in detail the computational and communication complexity properties of both algorithms theoretically and also through implementations. We conclude the paper with a discussion on computational privacy and other notions of privacy such as the non-unique retrieval of the private information from the protocol outputs.


Privacy Guarantees for Cloud-based State Estimation using Partially Homomorphic Encryption

The privacy aspect of state estimation algorithms has been drawing high ...

Crypto-Nets: Neural Networks over Encrypted Data

The problem we address is the following: how can a user employ a predict...

Secure Multi-party Computation for Cloud-based Control

In this chapter, we will explore the cloud-outsourced privacy-preserving...

Optimal Accuracy-Privacy Trade-Off for Secure Multi-Party Computations

The purpose of Secure Multi-Party Computation is to enable protocol part...

Efficient Cloud-based Secret Shuffling via Homomorphic Encryption

When working with joint collections of confidential data from multiple s...

SoK: Fully Homomorphic Encryption Compilers

Fully Homomorphic Encryption (FHE) allows a third party to perform arbit...

SafeComp: Protocol For Certifying Cloud Computations Integrity

We define a problem of certifying computation integrity performed by som...