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Papers

Byzantine-Robust Aggregation for Securing Decentralized Federated Learning
Sep 26, 2024Diego Cajaraville-Aboy, Ana Fernández-Vilas, Rebeca P. Díaz-Redondo +1Federated Learning Byzantine Attacks
TiROD: Tiny Robotics Dataset and Benchmark for Continual Object Detection
Sep 24, 2024Francesco Pasti, Riccardo De Monte, Davide Dalle Pezze +2Robotic Datasets Efficient Continual Learning
Generation of Uncertainty-Aware High-Level Spatial Concepts in Factorized 3D Scene Graphs via Graph Neural Networks
Sep 18, 2024Jose Andres Millan-Romera, Muhammad Shaheer, Miguel Fernandez-Cortizas +33D Scene Graphs Orb-Slam2
PSHuman: Photorealistic Single-image 3D Human Reconstruction using Cross-Scale Multiview Diffusion and Explicit Remeshing
Sep 16, 2024Peng Li, Wangguandong Zheng, Yuan Liu +9Avatar Reconstruction Multi-View Diffusion Model
MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning
Sep 9, 2024Jianyi Zhang, Hao Frank Yang, Ang Li +5Multi-Modal Large Language Models Cross-Modal Learning
Therapy as an NLP Task: Comparing LLMs and Human Peers Behaviors in CBT Sessions
Sep 3, 2024Zainab Iftikhar, Sean Ransom, Amy Xiao +2Cognitive Behavioral Therapy
Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models
Sep 1, 2024Martin Mayr, Marcel Dreier, Florian Kordon +5Handwritten Text Recognition Handwriting
DeepSPoC: A Deep Learning Based Sequential Propagation of Chaos
Aug 29, 2024Kai Du, Yongle Xie, Tao Zhou +1Neural Partial Differential Equation Solvers Physical Dynamics
TrafficGamer: Reliable and Flexible Traffic Simulation for Safety-Critical Scenarios with Game-Theoretic Oracles
Aug 28, 2024Guanren Qiao, Guorui Quan, Jiawei Yu +2Microscopic Traffic Simulations Autonomous Driving
ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data
Aug 28, 2024Weizhou Wang, Eric Liu, Xiangyu Guo +3Vulnerability Detection & Repair Vulnerable Code
A Simulation Framework for Electromagnetic Signal Injection Attacks on Image Sensors
Aug 9, 2024Youqian Zhang, MK Michael Cheung, Chunxi Yang +6
Achieving More with Less: A Tensor-Optimization-Powered Ensemble Method
Aug 6, 2024Jinghui Yuan, Weijin Jiang, Zhe Cao +4
Autoencoders in Function Space
Aug 2, 2024Justin Bunker, Mark Girolami, Hefin Lambley +2Variational Autoencoder Masked Autoencoders
Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition
Aug 2, 2024Róisín Luo, James McDermott, Colm O'RiordanMechanistic Interpretability Perturbations
ProSpec RL: Plan Ahead, then Execute
Jul 31, 2024Liangliang Liu, Yi Guan, BoRan Wang +5Model-Free Reinforcement Learning Deep Reinforcement Learning
MambaCapsule: Towards Transparent Cardiac Disease Diagnosis with Electrocardiography Using Mamba Capsule Network
Jul 30, 2024Yinlong Xu, Zitai Kong, Yixuan Wu +5Electrocardiogram Classification Congenital Heart Disease
Small Molecule Optimization with Large Language Models
Jul 26, 2024Philipp Guevorguian, Menua Bedrosian, Tigran Fahradyan +3Molecular Optimization Drug Discovery
Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms
Jul 21, 2024Sheila Schoepp, Mehran Taghian, Shotaro Miwa +3Fault Tolerance Agent Framework
Unexplainability of Artificial Intelligence Judgments and Functional Implementation in Kant's Perspective
Jul 12, 2024Jongwoo SeoHuman Judgment Epistemic Stance
A Generalization Bound for Nearly-Linear Networks
Jul 9, 2024Eugene GolikovGeneralization Bounds Neural Network
SSP-GNN: Learning to Track via Bilevel Optimization
Jul 5, 2024Griffin Golias, Masa Nakura-Fan, Vitaly AblavskyMulti-Object Tracking
Event-based vision sensing and its application to pedestrian detection for intelligent transportation and surveillance
Jul 5, 2024Han Wang, Juntao Wu, Jingyuan Bao +5Pedestrian Detection Vision Sensors
Toward Secure Code Generation: Bridging Correctness and Security via Task-Adaptive Vulnerability Modeling and Execution-Based Benchmarking
Jul 2, 2024Jiexin Wang, Liuwen Cao, Xitong Luo +6Code Generation Large Language Model Safety
Decision-Centered Abstractions via Orthogonal Estimation of Difference-of-Q Functions
Jun 12, 2024Defu Cao, Angela ZhouOffline Reinforcement Learning Abstraction
Lifelong Learning of Video Diffusion Models From a Single Video Stream
Jun 7, 2024Jason Yoo, Yingchen He, Saeid Naderiparizi +4
GENIE: Watermarking Graph Neural Networks for Link Prediction
Jun 7, 2024Venkata Sai Pranav Bachina, Aaryan Ajay Sharma, Ankit Gangwal +1Graph Neural Networks Zero-Shot Link Prediction
Grammar-Aligned Decoding
May 31, 2024Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick +2Large Language Model Generation Code Generation
Privacy-Aware Visual Language Models
May 27, 2024Laurens Samson, Nimrod Barazani, Sennay Ghebreab +1Large Vision Language Models Vision-Language
EM-GANSim: Real-time and Accurate EM Simulation Using Conditional GANs for 3D Indoor Scenes
May 27, 2024Ruichen Wang, Dinesh ManochaEmulators Dual-Domain Equivariant Generative Adversarial Network
Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees
May 26, 2024Yilei Chen, Vittorio Giammarino, James Queeney +1Off-Policy Evaluation Imitation Learning

Sep 26, 2024 · cs.LGJ/K move · Enter open · S save

Byzantine-Robust Aggregation for Securing Decentralized Federated Learning

Diego Cajaraville-Aboy, Ana Fernández-Vilas, Rebeca P. Díaz-Redondo, Manuel Fernández-Veiga

atlanTTic Research Center – ICLAB – Universidade de Vigo, Vigo, 36310, Spain

Federated Learning (FL) emerges as a distributed machine learning approach that addresses privacy concerns by training AI models locally on devices. Decentralized Federated Learning (DFL) extends the FL paradigm by eliminating the central server, thereby enhancing scalability and robustness through the avoidance of a single point of failure. However, DFL faces significant challenges in optimizing security, as most Byzantine-robust algorithms proposed in the literature are designed for centralized scenarios. In this paper, we present a novel Byzantine-robust aggregation algorithm to enhance the security of Decentralized Federated Learning environments, coined WFAgg. This proposal handles adverse conditions and strengthens the robustness of dynamic decentralized topologies at the same time by employing multiple filters to identify and mitigate Byzantine attacks. Experimental results demonstrate the effectiveness of the proposed algorithm in maintaining model accuracy and convergence in the presence of various Byzantine attack scenarios, outperforming state-of-the-art centralized Byzantine-robust aggregation schemes (such as Multi-Krum or Clustering). These algorithms are evaluated on an IID image classification problem in both centralized and decentralized scenarios.

Federated Learning Byzantine Attacks Decentralization

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