21 research outputs found
Private Computation of Polynomials over Networks
This study concentrates on preserving privacy in a network of agents where
each agent seeks to evaluate a general polynomial function over the private
values of her immediate neighbors. We provide an algorithm for the exact
evaluation of such functions while preserving privacy of the involved agents.
The solution is based on a reformulation of polynomials and adoption of two
cryptographic primitives: Paillier as a Partially Homomorphic Encryption scheme
and multiplicative-additive secret sharing. The provided algorithm is fully
distributed, lightweight in communication, robust to dropout of agents, and can
accommodate a wide class of functions. Moreover, system theoretic and secure
multi-party conditions guaranteeing the privacy preservation of an agent's
private values against a set of colluding agents are established. The
theoretical developments are complemented by numerical investigations
illustrating the accuracy of the algorithm and the resulting computational
cost.Comment: 11 pages, 2 figure
Private Computation of Polynomials over Networks
This study concentrates on preserving privacy in a network of agents where
each agent seeks to evaluate a general polynomial function over the private
values of her immediate neighbors. We provide an algorithm for the exact
evaluation of such functions while preserving privacy of the involved agents.
The solution is based on a reformulation of polynomials and adoption of two
cryptographic primitives: Paillier as a Partially Homomorphic Encryption scheme
and multiplicative-additive secret sharing. The provided algorithm is fully
distributed, lightweight in communication, robust to dropout of agents, and can
accommodate a wide class of functions. Moreover, system theoretic and secure
multi-party conditions guaranteeing the privacy preservation of an agent's
private values against a set of colluding agents are established. The
theoretical developments are complemented by numerical investigations
illustrating the accuracy of the algorithm and the resulting computational
cost.Comment: 11 pages, 2 figure
Secure and Private Implementation of Dynamic Controllers Using Semi-Homomorphic Encryption
This paper presents a secure and private implementation of linear
time-invariant dynamic controllers using Paillier's encryption, a
semi-homomorphic encryption method. To avoid overflow or underflow within the
encryption domain, the state of the controller is reset periodically. A control
design approach is presented to ensure stability and optimize performance of
the closed-loop system with encrypted controller.Comment: Improved numerical exampl
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 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
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
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
Encrypted control for networked systems -- An illustrative introduction and current challenges
Cloud computing and distributed computing are becoming ubiquitous in many
modern control systems such as smart grids, building automation, robot swarms
or intelligent transportation systems. Compared to "isolated" control systems,
the advantages of cloud-based and distributed control systems are, in
particular, resource pooling and outsourcing, rapid scalability, and high
performance. However, these capabilities do not come without risks. In fact,
the involved communication and processing of sensitive data via public networks
and on third-party platforms promote, among other cyberthreats, eavesdropping
and manipulation of data. Encrypted control addresses this security gap and
provides confidentiality of the processed data in the entire control loop. This
paper presents a tutorial-style introduction to this young but emerging field
in the framework of secure control for networked dynamical systems.Comment: The paper is a preprint of an accepted paper in the IEEE Control
Systems Magazin
Secure Teleoperation Control Using Somewhat Homomorphic Encryption
Presented at 2022 Modeling, Estimation, and Control Conference (MECC) , October 2022The goal of this research is to establish control theoretic methods to enhance cyber security of networked motion control systems by utilizing somewhat homomorphic encryption. The proposed approach will encrypt the entire motion control schemes including: sensor signals, model parameters, feedback gains, and performs computation in the ciphertext space to generate motion commands to servo systems without a security hole. The paper will discuss implementation of encrypted bilateral teleoperation control schemes with nonlinear friction compensation. The paper will present (1) encrypted teleoperation control realization with somewhat homomorphic encryption and (2) simulation results.This work was supported in part by the National Science Foundation under Grant No. 2112793 and the Japan Society for the Promotion of Science KAKENHI Grant No. JP22H01509
Fully Homomorphic Encryption-enabled Distance-based Distributed Formation Control with Distance Mismatch Estimators
This paper considers the use of fully homomorphic encryption for the realisation of distributed formation control of multi-agent systems via edge computer. In our proposed framework, the distributed control computation in the edge computer uses only the encrypted data without the need for a reset mechanism that is commonly required to avoid error accumulation. Simulation results show that, despite the use of encrypted data on the controller and errors introduced by the quantization process prior to the encryption, the formation is able to converge to the desired shape. The proposed architecture offers insight on the mechanism for realising distributed control computation in an edge/cloud computer while preserving the privacy of local information coming from each agent