Cover Image

Privacy-preserving gradient-based fair federated learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Adamek, Janis, Darup, Moritz Schulze
Format:	Preprint
Published:	2024
Subjects:	Machine Learning 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

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)

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

Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation
by: von der Heyden, Jonas, et al.
Published: (2024)

A review of federated learning in renewable energy applications: Potential, challenges, and future directions
by: Grataloup, Albin, et al.
Published: (2023)

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

Privacy-Preserving Data Fusion for Traffic State Estimation: A Vertical Federated Learning Approach
by: Wang, Qiqing, et al.
Published: (2024)

ZTFed-MAS2S: A Zero-Trust Federated Learning Framework with Verifiable Privacy and Trust-Aware Aggregation for Wind Power Data Imputation
by: Li, Yang, et al.
Published: (2025)

Privacy-preserving quantum federated learning via gradient hiding
by: Li, Changhao, et al.
Published: (2023)

Enhancing Network Security Management in Water Systems using FM-based Attack Attribution
by: Avdalovic, Aleksandar, et al.
Published: (2025)

FedDCL: a federated data collaboration learning as a hybrid-type privacy-preserving framework based on federated learning and data collaboration
by: Imakura, Akira, et al.
Published: (2024)

Real-Time Zero-Day Intrusion Detection System for Automotive Controller Area Network on FPGAs
by: Khandelwal, Shashwat, et al.
Published: (2024)

A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs
by: Khandelwal, Shashwat, et al.
Published: (2024)

Amalgam: A Framework for Obfuscated Neural Network Training on the Cloud
by: Taki, Sifat Ut, et al.
Published: (2024)

A Multi-module Robust Method for Transient Stability Assessment against False Label Injection Cyberattacks
by: Wang, Hanxuan, et al.
Published: (2024)

An Adversarial Approach to Evaluating the Robustness of Event Identification Models
by: Bahwal, Obai, et al.
Published: (2024)

Localization of Dummy Data Injection Attacks in Power Systems Considering Incomplete Topological Information: A Spatio-Temporal Graph Wavelet Convolutional Neural Network Approach
by: Qu, Zhaoyang, et al.
Published: (2024)

Temporal assessment of malicious behaviors: application to turnout field data monitoring
by: Abdellaoui, Sara, et al.
Published: (2024)

ANALYSE -- Learning to Attack Cyber-Physical Energy Systems With Intelligent Agents
by: Wolgast, Thomas, et al.
Published: (2023)

Scalable Learning of Intrusion Responses through Recursive Decomposition
by: Hammar, Kim, et al.
Published: (2023)

Random Walk Learning and the Pac-Man Attack
by: Chen, Xingran, et al.
Published: (2025)

Neural Network-Based Detection and Multi-Class Classification of FDI Attacks in Smart Grid Home Energy Systems
by: Sen, Varsha, et al.
Published: (2025)

Efficient Implementation of Reinforcement Learning over Homomorphic Encryption
by: Suh, Jihoon, et al.
Published: (2025)

Breaking and Fixing Defenses Against Control-Flow Hijacking in Multi-Agent Systems
by: Jha, Rishi, et al.
Published: (2025)

A Kolmogorov-Arnold Network for Interpretable Cyberattack Detection in AGC Systems
by: Jilan, Jehad, et al.
Published: (2025)

Privacy-preserving data release leveraging optimal transport and particle gradient descent
by: Donhauser, Konstantin, et al.
Published: (2024)

Differentially Private High Dimensional Bandits
by: Shukla, Apurv
Published: (2024)

A Lightweight FPGA-based IDS-ECU Architecture for Automotive CAN
by: Khandelwal, Shashwat, et al.
Published: (2024)

Hacking Predictors Means Hacking Cars: Using Sensitivity Analysis to Identify Trajectory Prediction Vulnerabilities for Autonomous Driving Security
by: Gibson, Marsalis, et al.
Published: (2024)

Privacy-preserving machine learning for healthcare: open challenges and future perspectives
by: Guerra-Manzanares, Alejandro, et al.
Published: (2023)

Can large language models be privacy preserving and fair medical coders?
by: Dadsetan, Ali, et al.
Published: (2024)

Differential Privacy via Distributionally Robust Optimization
by: Selvi, Aras, et al.
Published: (2023)

Design of Stochastic Quantizers for Privacy Preservation
by: Liu, Le, et al.
Published: (2024)

Faithful and Privacy-Preserving Implementation of Average Consensus
by: Teranishi, Kaoru, et al.
Published: (2025)

Quantised Neural Network Accelerators for Low-Power IDS in Automotive Networks
by: Khandelwal, Shashwat, et al.
Published: (2024)

Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN
by: Khandelwal, Shashwat, et al.
Published: (2024)

FTA generation using GenAI with an Autonomy sensor Usecase
by: Shetiya, Sneha Sudhir, et al.
Published: (2024)

An Unsupervised Adversarial Autoencoder for Cyber Attack Detection in Power Distribution Grids
by: Zideh, Mehdi Jabbari, et al.
Published: (2024)

Unmasking Covert Intrusions: Detection of Fault-Masking Cyberattacks on Differential Protection Systems
by: Saber, Ahmad Mohammad, et al.
Published: (2024)

Designing Robust Cyber-Defense Agents with Evolving Behavior Trees
by: Potteiger, Nicholas, et al.
Published: (2024)