A PHP Error was encountered

Severity: Warning

Message: unlink(/var/www/html/application/cache/pagemenu-desktop): No such file or directory

Filename: drivers/Cache_file.php

Line Number: 279

Backtrace:

File: /var/www/html/application/models/Menu_model.php
Line: 43
Function: get

File: /var/www/html/application/libraries/Managelayout.php
Line: 197
Function: get_all_menu

File: /var/www/html/application/controllers/Board_post.php
Line: 940
Function: front

File: /var/www/html/application/core/CB_Controller.php
Line: 109
Function: post

File: /var/www/html/index.php
Line: 349
Function: require_once

VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification, ESORICS 2024 > International Papers - 서울대학교연구원

[AI Security] VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification, ESORICS 2024

VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification

Yungi Cho, Woorim Han, Miseon Yu, Younghan Lee, Ho Bae* and Yunheung Paek*

European Symposium on Research in Computer Security (ESORICS) 2024

∗ : Correspondence should be addressed to H. Bae and Y. Peak

0
 0
목록 답변 이전글 다음글

International Papers

Privacy Enhancing Computing Design Space Exploration of Efficient FPGA-based Accelerators for Homomorphically Encrypted CNN Inference, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems(TCAD), Oct 2026 Hot
Privacy Enhancing Computing PCPSI: Efficient Unbalanced Private Set Intersection Using Homomorphic Encryption with Plaintext–Ciphertext Multiplication, IEEE Access, May 2026
Privacy Enhancing Computing HEPIC: Private Inference over Homomorphic Encryption with Client Intervention, ASPLOS 2026
Privacy Enhancing Computing Towards an Efficient Dataflow-flexible Accelerator by Finding Optimal Dataflows of DNNs, Future Generation Computer Systems, Sep 2025
Privacy Enhancing Computing An Accelerator for Low-computational Overhead Privacy-Preserving GNN Inference, HiPC 2025
Privacy Enhancing Computing SLOTHE: Lazy Approximation of Non-Arithmetic Neural Network Functions over Encrypted Data, USENIX Security 2025
Privacy Enhancing Computing Affinity-based Optimizations for TFHE on Processing-in-DRAM, ASPLOS 2025 Affinity-based Optimizations for TFHE on Processing-in-DRAM, ASPLOS 2025
Privacy Enhancing Computing LOHEN: Layer-wise Optimizations for Neural Network Inferences over Encrypted Data with high Performance or Accuracy, USENIX Security 2025
Privacy Enhancing Computing Affinity-based Optimizations of Homomorphic Encryption Operations on Processing-in-DRAM, DAC WIP 2024
목록

© Copyright ⓒ 2011~2018 by SOR Lab. All Rights Reserved.
SOR Lab., Department of Electrical and Computer Engineering,
Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea