Cover Image

Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	von der Heyden, Jonas, Schlüter, Nils, Binfet, Philipp, Asman, Martin, Zdrallek, Markus, Jager, Tibor, Darup, Moritz Schulze
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Encrypted system identification as-a-service via reliable encrypted matrix inversion
by: Adamek, Janis, et al.
Published: (2024)

On the (non-)resilience of encrypted controllers to covert attacks
by: Binfet, Philipp, et al.
Published: (2026)

On the design of stabilizing FIR controllers
by: Adamek, Janis, et al.
Published: (2024)

Privacy-preserving gradient-based fair federated learning
by: Adamek, Janis, et al.
Published: (2024)

Towards privacy-preserving cooperative control via encrypted distributed optimization
by: Binfet, Philipp, et al.
Published: (2024)

SPOQchain: Platform for Secure, Scalable, and Privacy-Preserving Supply Chain Tracing and Counterfeit Protection
by: Finke, Moritz, et al.
Published: (2024)

Efficient and Privacy-Preserving Binary Dot Product via Multi-Party Computation
by: Dehkordi, Fatemeh Jafarian, et al.
Published: (2025)

Privacy-Preserving Distributed Optimization Under Time Constraints Using Secure Multi-Party Computation and Evolutionary Algorithms
by: Gruber, Sebastian, et al.
Published: (2026)

On the Communication Complexity of Secure Multi-Party Computation With Aborts
by: Bartusek, James, et al.
Published: (2024)

Applications of Secure Multi-Party Computation in Financial Services
by: Sedraoui, Brahim Khalil, et al.
Published: (2026)

Privacy-Preserving Quantum Two-Party Geometric Intersection
by: Liu, Wen-Jie, et al.
Published: (2023)

Verifiable Privacy-Preserving Computing
by: Bontekoe, Tariq, et al.
Published: (2023)

A Response to: A Note on "Privacy Preserving n-Party Scalar Product Protocol"
by: van Daalen, Florian, et al.
Published: (2024)

Generative AI for Secure and Privacy-Preserving Mobile Crowdsensing
by: Yang, Yaoqi, et al.
Published: (2024)

SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud
by: Duan, Shijin, et al.
Published: (2024)

Accelerating Privacy-Preserving Medical Record Linkage: A Three-Party MPC Approach
by: Mağara, Şeyma Selcan, et al.
Published: (2024)

Secure and Efficient $L^p$-Norm Computation for Two-Party Learning Applications
by: Arastehfard, Ali, et al.
Published: (2025)

Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning
by: Behnia, Rouzbeh, et al.
Published: (2023)

Secure and Privacy-Preserving Authentication for Data Subject Rights Enforcement
by: Hansen, Malte, et al.
Published: (2024)

Preserving Privacy and Security in Federated Learning
by: Nguyen, Truc, et al.
Published: (2022)

Experimental Examination of Secure Two-Party Controller Computation
by: Teranishi, Kaoru, et al.
Published: (2026)

A Survey on Privacy-Preserving Computing in the Automotive Domain
by: Yuca, Nergiz, et al.
Published: (2025)

Privacy-Preserving Patient Identity Management Framework for Secure Healthcare Access
by: Muslim, Nasif, et al.
Published: (2026)

Quantum-Secure Certificate-Less Conditional Privacy-Preserving Authentication for VANET
by: Verma, Girraj Kumar, et al.
Published: (2024)

PACCOR4ESP: Embedded Device Security Attestation using Platform Attribute Certificates
by: Grübl, Thomas, et al.
Published: (2024)

A Scheduling-Aware Defense Against Prefetching-Based Side-Channel Attacks
by: Schlüter, Till, et al.
Published: (2024)

Byzantine-Secure Relying Party for Resilient RPKI
by: Friess, Jens, et al.
Published: (2024)

Security and Privacy Management of IoT Using Quantum Computing
by: Sen, Jaydip
Published: (2025)

Client-Aided Secure Two-Party Computation of Dynamic Controllers
by: Teranishi, Kaoru, et al.
Published: (2025)

Enhancing Security Using Random Binary Weights in Privacy-Preserving Federated Learning
by: Sawada, Hiroto, et al.
Published: (2024)

Secure Multi-Key Homomorphic Encryption with Application to Privacy-Preserving Federated Learning
by: Wu, Jiahui, et al.
Published: (2025)

Privacy-Preserving and Secure Spectrum Sharing for Database-Driven Cognitive Radio Networks
by: Darzi, Saleh, et al.
Published: (2026)

Practical Privacy-Preserving Identity Verification using Third-Party Cloud Services and FHE (Role of Data Encoding in Circuit Depth Management)
by: Mohan, Deep Inder, et al.
Published: (2024)

OPAF: Optimized Secure Two-Party Computation Protocols for Nonlinear Activation Functions in Recurrent Neural Network
by: Feng, Qian, et al.
Published: (2024)

Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation
by: Saleem, Hamza, et al.
Published: (2024)

IDPFilter: Mitigating Interdependent Privacy Issues in Third-Party Apps
by: Liu, Shuaishuai, et al.
Published: (2024)

Towards Securing IIoT: An Innovative Privacy-Preserving Anomaly Detector Based on Federated Learning
by: Poorazad, Samira Kamali, et al.
Published: (2026)

Commitment Schemes for Multi-Party Computation
by: Ionescu, Ioan, et al.
Published: (2025)

The Security and Privacy of Mobile Edge Computing: An Artificial Intelligence Perspective
by: Wang, Cheng, et al.
Published: (2024)

Empirical Security Analysis of Software-based Fault Isolation through Controlled Fault Injection
by: Bars, Nils, et al.
Published: (2025)