Cover Image

PackVFL: Efficient HE Packing for Vertical Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Liu, Cai, Shuowei, Chai, Di, Zhang, Junxue, Tian, Han, Jin, Yilun, Guo, Kun, Chen, Kai, Yang, Qiang
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Survey for Federated Learning Evaluations: Goals and Measures
by: Chai, Di, et al.
Published: (2023)

HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning
by: Qiu, Pengyu, et al.
Published: (2022)

Accelerating Vertical Federated Learning
by: Cai, Dongqi, et al.
Published: (2022)

Adversarially Robust Assembly Language Model for Packed Executables Detection
by: Li, Shijia, et al.
Published: (2025)

High-Throughput and Scalable Secure Inference Protocols for Deep Learning with Packed Secret Sharing
by: Zhang, Qinghui, et al.
Published: (2026)

PackHero: A Scalable Graph-based Approach for Efficient Packer Identification
by: Di Gennaro, Marco, et al.
Published: (2025)

Hermes: Efficient Global Homomorphic Aggregation over Mutable Packed Ciphertexts
by: Zhao, Dongfang
Published: (2025)

Packed Malware Detection Using Grayscale Binary-to-Image Representations
by: Alkhateeb, Ehab, et al.
Published: (2025)

SmmPack: Obfuscation for SMM Modules with TPM Sealed Key
by: Matsuo, Kazuki, et al.
Published: (2024)

UIFV: Data Reconstruction Attack in Vertical Federated Learning
by: Yang, Jirui, et al.
Published: (2024)

Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning
by: Nie, Chenfei, et al.
Published: (2024)

Pack-A-Mal: A Malware Analysis Framework for Open-Source Packages
by: Vu, Duc-Ly, et al.
Published: (2025)

Privacy-preserving Preselection for Face Identification Based on Packing
by: Xin, Rundong, et al.
Published: (2025)

Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems
by: Gibert, Daniel, et al.
Published: (2024)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)

FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System
by: Jin, Weizhao, et al.
Published: (2023)

SoK: Fully Homomorphic Encryption Accelerators
by: Zhang, Junxue, et al.
Published: (2022)

VMask: Tunable Label Privacy Protection for Vertical Federated Learning via Layer Masking
by: Tan, Juntao, et al.
Published: (2025)

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM
by: Xie, Chulin, et al.
Published: (2022)

FedGMark: Certifiably Robust Watermarking for Federated Graph Learning
by: Yang, Yuxin, et al.
Published: (2024)

LADSG: Label-Anonymized Distillation and Similar Gradient Substitution for Label Privacy in Vertical Federated Learning
by: Yan, Zeyu, et al.
Published: (2025)

Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion
by: Zhang, Xiaojin, et al.
Published: (2023)

FedBit: Accelerating Privacy-Preserving Federated Learning via Bit-Interleaved Packing and Cross-Layer Co-Design
by: Meng, Xiangchen, et al.
Published: (2025)

Packing Entries to Diagonals for Homomorphic Sparse-Matrix Vector Multiplication
by: Mutluergil, Kemal, et al.
Published: (2026)

PackMonitor: Enabling Zero Package Hallucinations Through Decoding-Time Monitoring
by: Liu, Xiting, et al.
Published: (2026)

FastFHE: Packing-Scalable and Depthwise-Separable CNN Inference Over FHE
by: Song, Wenbo, et al.
Published: (2025)

Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses
by: Yang, Yuxin, et al.
Published: (2024)

Bilateral Differentially Private Vertical Federated Boosted Decision Trees
by: Zhang, Bokang, et al.
Published: (2025)

Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation
by: Yang, Kun, et al.
Published: (2025)

FLASH-FHE: A Heterogeneous Architecture for Fully Homomorphic Encryption Acceleration
by: Zhang, Junxue, et al.
Published: (2025)

Efficient Byzantine-Robust Privacy-Preserving Federated Learning via Dimension Compression
by: Qin, Xian, et al.
Published: (2025)

VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication
by: Yuan, Xun, et al.
Published: (2024)

A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in Federated Learning
by: Yang, Yuxin, et al.
Published: (2024)

HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning
by: He, Weiyang, et al.
Published: (2025)

HyPHEN: A Hybrid Packing Method and Optimizations for Homomorphic Encryption-Based Neural Networks
by: Kim, Donghwan, et al.
Published: (2023)

Enhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense
by: Li, Wenjie, et al.
Published: (2024)

Secure and Privacy-Preserving Vertical Federated Learning
by: Jin, Shan, et al.
Published: (2026)

Efficient Privacy-Preserving Cross-Silo Federated Learning with Multi-Key Homomorphic Encryption
by: Omar, Abdullah Al, et al.
Published: (2025)

Improving Efficiency in Federated Learning with Optimized Homomorphic Encryption
by: Yang, Feiran
Published: (2025)

MedHE: Communication-Efficient Privacy-Preserving Federated Learning with Adaptive Gradient Sparsification for Healthcare
by: Yesmin, Farjana
Published: (2025)