Results 51 to 60 of about 111,433 (205)

Toward Encrypted OPF Across Transmission and Distribution—Prospects and Open Problems of Encrypted Quadratic Programming

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT The increasing integration of distributed energy resources demands enhanced coordination between transmission system operators (TSOs) and distribution system operators (DSOs) to maintain reliable grid operation. Traditional approaches rely on hierarchical or distributed optimization schemes for power flow management, but these methods either ...
Janis Adamek, Philipp Binfet, Maísa Beraldo Bandeira, Timm Faulwasser, Moritz Schulze Darup   +4 more
wiley   +1 more source

Privacy‐Preserving Data‐Driven Distributed MPC for Heterogeneous Nonlinear Multi‐Agent Systems

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Distributed model predictive control (DMPC) is a cornerstone for coordinating multi‐agent systems, yet simultaneously ensuring data privacy, handling unknown nonlinear dynamics, and managing heterogeneous constraints remains an open challenge.
Mahmood Mazare, Hossein Ramezani
wiley   +1 more source

Homomorphic Encryption and Applications

, 2014
Preface Homomorphic encryption is a form of encryption that allows specific types of computations to be carried out on ciphertext and generate an encrypted result that, when decrypted, matches the result of operations performed on the plaintext.
Bertino, Elisa, Yi, Xun, Paulet, Russell
core   +1 more source

Frequency Shaping for Improving a Trade‐Off Between Control and Privacy Performance: Beyond Differential Privacy

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In privacy protection of control systems, a trade‐off between control performance and privacy level is often pointed out. Our goal in this paper is to improve this trade‐off by shaping the frequency of noise added for privacy protection when the control objective is to track a reference signal, which is taken as a piece of information whose ...
Rintaro Watanabe, Yu Kawano, Nobutaka Wada, Ming Cao   +3 more
wiley   +1 more source

Initial State Privacy of Nonlinear Systems on Riemannian Manifolds

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley   +1 more source

Exact Homomorphic Encryption

CoRR
Inspired by the concept of fault tolerance quantum computation, this article proposes a framework dubbed Exact Homomorphic Encryption, EHE, enabling exact computations on encrypted data without the need for pre-decryption. The introduction of quantum gates is a critical step for constructing the message encryption and the computation encryption within ...
Zheng-Yao Su, Ming-Chung Tsai
openaire   +2 more sources

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha, Mohammad Kamrul Hasan, Shayla Islam, Shailesh Khapre, Salwani Abdullah, Taher M. Ghazal, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nguyen Vo, Md Akhtaruzzaman   +9 more
wiley   +1 more source

Homomorphic encryption and coding theory [PDF]

, 2012
Title: Homomorphic encryption and coding theory Author: Veronika Půlpánová Department: Department of algebra Supervisor: RNDr. Michal Hojsík, Ph.D., Department of algebra Abstract: The current mainstream in fully homomorphic encryption is the appro- ach ...
Půlpánová, Veronika
core   +1 more source

PPEPV‐RDL: Achieving Privacy‐Preserving, Efficient, Publicly Verifiable Rational Delegation Learning

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Delegation learning is an implementation approach within privacy‐preserving machine learning (PPML). It refers to that the delegator outsources the training task to servers with strong computing power due to its own limited computing resources, and the servers return the correct training results and get the service revenue.
Xinyu Zhang, Zerui Chen, Youliang Tian, Jinbo Xiong, Jianfeng Ma   +4 more
wiley   +1 more source

Simulation-Based Performance Validation of Homomorphic Encryption Algorithms in the Internet of Things

Future Internet, 2019
IoT systems consist of Hardware/Software systems (e.g., sensors) that are embedded in a physical world, networked and that interact with complex software platforms.
Johannes Kölsch, Christopher Heinz, Axel Ratzke, Christoph Grimm   +3 more
doaj   +1 more source