GuardianMPC: Backdoor-Resilient Neural Network Computation

GuardianMPC: Backdoor-Resilient Neural Network Computation

The rapid growth of deep learning (DL) has raised serious concerns about users’ data and neural network (NN) models’ security and privacy, particularly the risk of backdoor insertion when outsourcing the training or employing pre-trained models. To ensure resilience against suc...

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Bibliographic Details
Main Authors: Mohammad Hashemi, Domenic Forte, Fatemeh Ganji
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Backdoor insertion
malicious adversary
neural networks
multiparty computation
secure and private function evaluation
private training
Online Access:https://ieeexplore.ieee.org/document/10836681/
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https://ieeexplore.ieee.org/document/10836681/

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