Copertina

Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chow, Ka-Ho, Wei, Wenqi, Yu, Lei
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Cryptography and Security Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

On the Adversarial Robustness of Graph Neural Networks with Graph Reduction
di: Wu, Kerui, et al.
Pubblicazione: (2024)

On the Robustness of Graph Reduction Against GNN Backdoor
di: Zhu, Yuxuan, et al.
Pubblicazione: (2024)

Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
di: Shan, Junjie, et al.
Pubblicazione: (2024)

On the Efficiency of Privacy Attacks in Federated Learning
di: Tabassum, Nawrin, et al.
Pubblicazione: (2024)

Stealthy and Adjustable Text-Guided Backdoor Attacks on Multimodal Pretrained Models
di: Zhang, Yiyang, et al.
Pubblicazione: (2026)

Building Gradient Bridges: Label Leakage from Restricted Gradient Sharing in Federated Learning
di: Zhang, Rui, et al.
Pubblicazione: (2024)

Harmless Backdoor-based Client-side Watermarking in Federated Learning
di: Luo, Kaijing, et al.
Pubblicazione: (2024)

BadRSSD: Backdoor Attacks on Regularized Self-Supervised Diffusion Models
di: Wang, Jiayao, et al.
Pubblicazione: (2026)

Backdoor Attacks on Discrete Graph Diffusion Models
di: Wang, Jiawen, et al.
Pubblicazione: (2025)

SteganoBackdoor: Stealthy and Data-Efficient Backdoor Attacks on Language Models
di: Xue, Eric, et al.
Pubblicazione: (2025)

Backdoored Retrievers for Prompt Injection Attacks on Retrieval Augmented Generation of Large Language Models
di: Clop, Cody, et al.
Pubblicazione: (2024)

BadMerging: Backdoor Attacks Against Model Merging
di: Zhang, Jinghuai, et al.
Pubblicazione: (2024)

UIBDiffusion: Universal Imperceptible Backdoor Attack for Diffusion Models
di: Han, Yuning, et al.
Pubblicazione: (2024)

Backdooring Masked Diffusion Language Models
di: Cao, Daniel Yiming, et al.
Pubblicazione: (2026)

Defending against Backdoor Attack on Deep Neural Networks
di: Cheng, Hao, et al.
Pubblicazione: (2020)

Composite Backdoor Attacks Against Large Language Models
di: Huang, Hai, et al.
Pubblicazione: (2023)

Persistent Backdoor Attacks in Continual Learning
di: Guo, Zhen, et al.
Pubblicazione: (2024)

Backdoor Attacks on Decentralised Post-Training
di: Ersoy, Oğuzhan, et al.
Pubblicazione: (2026)

Detecting Backdoor Attacks via Similarity in Semantic Communication Systems
di: Wei, Ziyang, et al.
Pubblicazione: (2025)

Unlearning Backdoor Attacks through Gradient-Based Model Pruning
di: Dunnett, Kealan, et al.
Pubblicazione: (2024)

Diff-Cleanse: Identifying and Mitigating Backdoor Attacks in Diffusion Models
di: Hao, Jiang, et al.
Pubblicazione: (2024)

Shortcuts Everywhere and Nowhere: Exploring Multi-Trigger Backdoor Attacks
di: Li, Yige, et al.
Pubblicazione: (2024)

Instruction Backdoor Attacks Against Customized LLMs
di: Zhang, Rui, et al.
Pubblicazione: (2024)

On the Out-of-Distribution Backdoor Attack for Federated Learning
di: Xu, Jiahao, et al.
Pubblicazione: (2025)

Backdoor Attacks in Peer-to-Peer Federated Learning
di: Syros, Georgios, et al.
Pubblicazione: (2023)

Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective
di: Chung, Ming-Yu, et al.
Pubblicazione: (2023)

Confundo: Learning to Generate Robust Poison for Practical RAG Systems
di: Hu, Haoyang, et al.
Pubblicazione: (2026)

CodePurify: Defend Backdoor Attacks on Neural Code Models via Entropy-based Purification
di: Mu, Fangwen, et al.
Pubblicazione: (2024)

State Backdoor: Towards Stealthy Real-world Poisoning Attack on Vision-Language-Action Model in State Space
di: Guo, Ji, et al.
Pubblicazione: (2026)

VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models
di: Chou, Sheng-Yen, et al.
Pubblicazione: (2023)

Watch Out for the Lifespan: Evaluating Backdoor Attacks Against Federated Model Adaptation
di: Vuillod, Bastien, et al.
Pubblicazione: (2025)

Adversarial Inception Backdoor Attacks against Reinforcement Learning
di: Rathbun, Ethan, et al.
Pubblicazione: (2024)

Backdoor Attacks on Transformers for Tabular Data: An Empirical Study
di: Pleiter, Bart, et al.
Pubblicazione: (2023)

Invariant Aggregator for Defending against Federated Backdoor Attacks
di: Wang, Xiaoyang, et al.
Pubblicazione: (2022)

Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning
di: Lee, Seohyun, et al.
Pubblicazione: (2025)

Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning
di: Lyu, Xiaoting, et al.
Pubblicazione: (2024)

Unlearn to Relearn Backdoors: Deferred Backdoor Functionality Attacks on Deep Learning Models
di: Shin, Jeongjin, et al.
Pubblicazione: (2024)

Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective
di: Zhang, Zhiwei, et al.
Pubblicazione: (2024)

DMGNN: Detecting and Mitigating Backdoor Attacks in Graph Neural Networks
di: Sui, Hao, et al.
Pubblicazione: (2024)

Krait: A Backdoor Attack Against Graph Prompt Tuning
di: Song, Ying, et al.
Pubblicazione: (2024)