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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

Showing 125 of 523 papers

TitleStatusHype
AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge BasesCode3
Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based AgentsCode3
Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based AgentsCode2
Backdoor Learning: A SurveyCode2
Test-Time Backdoor Attacks on Multimodal Large Language ModelsCode2
BAPLe: Backdoor Attacks on Medical Foundational Models using Prompt LearningCode2
BadChain: Backdoor Chain-of-Thought Prompting for Large Language ModelsCode2
An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong DetectionCode2
BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean LabelCode1
BadCLIP: Dual-Embedding Guided Backdoor Attack on Multimodal Contrastive LearningCode1
BadEdit: Backdooring large language models by model editingCode1
BadCM: Invisible Backdoor Attack Against Cross-Modal LearningCode1
Backdoor Attacks Against Dataset DistillationCode1
BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised LearningCode1
BadMerging: Backdoor Attacks Against Model MergingCode1
Backdoor Defense via Deconfounded Representation LearningCode1
Anti-Backdoor Learning: Training Clean Models on Poisoned DataCode1
Backdoor Attack with Sparse and Invisible TriggerCode1
Backdoor Attacks on Federated Learning with Lottery Ticket HypothesisCode1
Anti-Distillation Backdoor Attacks: Backdoors Can Really Survive in Knowledge DistillationCode1
Backdoor Attacks on Self-Supervised LearningCode1
Backdoor Attacks for Remote Sensing Data with Wavelet TransformCode1
Backdoor Attack against Speaker VerificationCode1
Can We Mitigate Backdoor Attack Using Adversarial Detection Methods?Code1
A new Backdoor Attack in CNNs by training set corruption without label poisoningCode1
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