Cover Image

Untargeted Adversarial Attack on Knowledge Graph Embeddings

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhao, Tianzhe, Chen, Jiaoyan, Ru, Yanchi, Lin, Qika, Geng, Yuxia, Liu, Jun
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RAG Safety: Exploring Knowledge Poisoning Attacks to Retrieval-Augmented Generation
by: Zhao, Tianzhe, et al.
Published: (2025)

Disttack: Graph Adversarial Attacks Toward Distributed GNN Training
by: Zhang, Yuxiang, et al.
Published: (2024)

Quantifying the Noise of Structural Perturbations on Graph Adversarial Attacks
by: Fang, Junyuan, et al.
Published: (2025)

A General Black-box Adversarial Attack on Graph-based Fake News Detectors
by: Zhu, Peican, et al.
Published: (2024)

Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
by: Mukherjee, Kunal, et al.
Published: (2026)

Vision Transformer with Adversarial Indicator Token against Adversarial Attacks in Radio Signal Classifications
by: Zhang, Lu, et al.
Published: (2025)

Adversarial Illusions in Multi-Modal Embeddings
by: Zhang, Tingwei, et al.
Published: (2023)

Heterogeneous Graph Backdoor Attack
by: Chen, Jiawei, et al.
Published: (2025)

FedGraM: Defending Against Untargeted Attacks in Federated Learning via Embedding Gram Matrix
by: Wu, Di, et al.
Published: (2025)

Untargeted Jailbreak Attack
by: Huang, Xinzhe, et al.
Published: (2025)

Relationship between Uncertainty in DNNs and Adversarial Attacks
by: Ogonna, Mabel, et al.
Published: (2024)

On the Robustness of Bayesian Neural Networks to Adversarial Attacks
by: Bortolussi, Luca, et al.
Published: (2022)

Adversarial Attacks on Transformers-Based Malware Detectors
by: Jakhotiya, Yash, et al.
Published: (2022)

Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts
by: Wu, Yuanwei, et al.
Published: (2023)

Mitigating the Structural Bias in Graph Adversarial Defenses
by: Fang, Junyuan, et al.
Published: (2025)

GenoArmory: A Unified Evaluation Framework for Adversarial Attacks on Genomic Foundation Models
by: Luo, Haozheng, et al.
Published: (2025)

Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs
by: Yuan, Leitao, et al.
Published: (2026)

MoCo-EA: Exploiting Adversarial Mode Connectivity for Efficient Evolutionary Attacks
by: Kim, Hyo Seo, et al.
Published: (2026)

Unlearning Inversion Attacks for Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2025)

Attacking LLMs and AI Agents: Advertisement Embedding Attacks Against Large Language Models
by: Guo, Qiming, et al.
Published: (2025)

On Membership Inference Attacks in Knowledge Distillation
by: Cui, Ziyao, et al.
Published: (2025)

Investigating Imperceptibility of Adversarial Attacks on Tabular Data: An Empirical Analysis
by: He, Zhipeng, et al.
Published: (2024)

Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
by: Yichao, Wu, et al.
Published: (2025)

Embedding Hidden Adversarial Capabilities in Pre-Trained Diffusion Models
by: Beerens, Lucas, et al.
Published: (2025)

Medusa: Cross-Modal Transferable Adversarial Attacks on Multimodal Medical Retrieval-Augmented Generation
by: Shang, Yingjia, et al.
Published: (2025)

Towards Robust Knowledge Unlearning: An Adversarial Framework for Assessing and Improving Unlearning Robustness in Large Language Models
by: Yuan, Hongbang, et al.
Published: (2024)

Adversarial Attacks on Reinforcement Learning-based Medical Questionnaire Systems: Input-level Perturbation Strategies and Medical Constraint Validation
by: Liu, Peizhuo
Published: (2025)

MF-CLIP: Leveraging CLIP as Surrogate Models for No-box Adversarial Attacks
by: Zhang, Jiaming, et al.
Published: (2023)

A White-Box Adversarial Attack Against a Digital Twin
by: Patterson, Wilson, et al.
Published: (2022)

Claudini: Autoresearch Discovers State-of-the-Art Adversarial Attack Algorithms for LLMs
by: Panfilov, Alexander, et al.
Published: (2026)

Practical Adversarial Attacks on Stochastic Bandits via Fake Data Injection
by: Zeng, Qirun, et al.
Published: (2025)

Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients
by: Yuan, Jinsheng, et al.
Published: (2025)

Frequency maps reveal the correlation between Adversarial Attacks and Implicit Bias
by: Basile, Lorenzo, et al.
Published: (2023)

Runtime Detection of Adversarial Attacks in AI Accelerators Using Performance Counters
by: Rahaman, Habibur, et al.
Published: (2025)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)

RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors
by: Bai, Fengshuo, et al.
Published: (2024)

Counter-Samples: A Stateless Strategy to Neutralize Black Box Adversarial Attacks
by: Bokobza, Roey, et al.
Published: (2024)

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting
by: Homaei, Mohammadhossein, et al.
Published: (2025)

UNDREAM: Bridging Differentiable Rendering and Photorealistic Simulation for End-to-end Adversarial Attacks
by: Phute, Mansi, et al.
Published: (2025)

AGSOA:Graph Neural Network Targeted Attack Based on Average Gradient and Structure Optimization
by: Chen, Yang, et al.
Published: (2024)