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Backdoor Attack

Backdoor attacks inject maliciously constructed data into a training set so that, at test time, the trained model misclassifies inputs patched with a backdoor trigger as an adversarially-desired target class.

Papers

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Showing 126–150 of 523 papers

TitleStatusHype
BAPLe: Backdoor Attacks on Medical Foundational Models using Prompt LearningCode2
Diff-Cleanse: Identifying and Mitigating Backdoor Attacks in Diffusion ModelsCode0
DeepBaR: Fault Backdoor Attack on Deep Neural Network Layers—0
BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning—0
Trading Devil Final: Backdoor attack via Stock market and Bayesian Optimization—0
Krait: A Backdoor Attack Against Graph Prompt Tuning—0
AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge BasesCode3
Uncertainty is Fragile: Manipulating Uncertainty in Large Language ModelsCode1
Backdoor Attacks against Image-to-Image Networks—0
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning—0
Evolutionary Trigger Detection and Lightweight Model Repair Based Backdoor Defense—0
BadCLM: Backdoor Attack in Clinical Language Models for Electronic Health Records—0
T2IShield: Defending Against Backdoors on Text-to-Image Diffusion ModelsCode1
Backdoor Graph CondensationCode0
SOS! Soft Prompt Attack Against Open-Source Large Language Models—0
Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks in Federated LearningCode0
Attack On Prompt: Backdoor Attack in Prompt-Based Continual Learning—0
Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift—0
CBPF: Filtering Poisoned Data Based on Composite Backdoor Attack—0
EmoAttack: Emotion-to-Image Diffusion Models for Emotional Backdoor Generation—0
Backdooring Bias into Text-to-Image ModelsCode0
Trading Devil: Robust backdoor attack via Stochastic investment models and Bayesian approach—0
Federated Learning with Flexible Architectures—0
An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong DetectionCode2
Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning—0
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