mlsanityData to 14 Oct 2026

Data Poisoning Attack against Knowledge Graph Embedding

arXiv 1904.12052 ↗First posted 26 Apr 2019cs.LG cs.AI cs.CRcited by 36

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Abstract (arXiv)

Knowledge graph embedding (KGE) is a technique for learning continuous embeddings for entities and relations in the knowledge graph.Due to its benefit to a variety of downstream tasks such as knowledge graph completion, question answering and recommendation, KGE has gained significant attention recently. Despite its effectiveness in a benign environment, KGE' robustness to adversarial attacks is not well-studied. Existing attack methods on graph data cannot be directly applied to attack the embeddings of knowledge graph due to its heterogeneity. To fill this gap, we propose a collection of data poisoning attack strategies, which can effectively manipulate the plausibility of arbitrary targeted facts in a knowledge graph by adding or deleting facts on the graph. The effectiveness and efficiency of the proposed attack strategies are verified by extensive evaluations on two widely-used benchmarks.

Key facts. Cited by 36 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Apr 2019.

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Citing papers per year: 2021: 4; 2022: 4; 2023: 6; 2024: 11; 2025: 7; 2026: 4.

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  1. 2022A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainabilitycited by 118
  2. 2022Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagationcited by 25
  3. 2025GraphRAG under Firecited by 24
  4. 2022A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protectioncited by 20
  5. 2021Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methodscited by 16
  6. 2021Universal Spectral Adversarial Attacks for Deformable Shapescited by 14
  7. 2021Poisoning Knowledge Graph Embeddings via Relation Inference Patternscited by 12
  8. 2023Analysis of Label-Flip Poisoning Attack on Machine Learning Based Malware Detectorcited by 11
  9. 2023It Is All About Data: A Survey on the Effects of Data on Adversarial Robustnesscited by 9
  10. 2021Task and Model Agnostic Adversarial Attack on Graph Neural Networkscited by 5
  11. 2023On the Security Risks of Knowledge Graph Reasoningcited by 5
  12. 2023Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise Detectioncited by 4
24 more
  1. 2022Random Walks for Adversarial Meshescited by 3
  2. 2024Fake Resume Attacks: Data Poisoning on Online Job Platformscited by 3
  3. 2024Untargeted Adversarial Attack on Knowledge Graph Embeddingscited by 3
  4. 2025Watermarking Graph Neural Networks via Explanations for Ownership Protectioncited by 3
  5. 2025RAG Safety: Exploring Knowledge Poisoning Attacks to Retrieval-Augmented Generationcited by 3
  6. 2024TWIG: Towards pre-hoc Hyperparameter Optimisation and Cross-Graph Generalisation via Simulated KGE Modelscited by 2
  7. 2024A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networkscited by 2
  8. 2024eXpath: Explaining Knowledge Graph Link Prediction with Ontological Closed Path Rulescited by 2
  9. 2026Making Theft Useless: Adulteration-Based Protection of Proprietary Knowledge Graphs in GraphRAG Systemscited by 2
  10. 2024KG4RecEval: Does Knowledge Graph Really Matter for Recommender Systems?cited by 1
  11. 2024Resilience in Knowledge Graph Embeddingscited by 1
  12. 2025KGMark: A Diffusion Watermark for Knowledge Graphscited by 1
  13. 2025Unifying Post-hoc Explanations of Knowledge Graph Completionscited by 1
  14. 2026ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflictscited by 1
  15. 2026Oracle Poisoning: Corrupting Knowledge Graphs to Weaponise AI Agent Reasoningcited by 1
  16. 2023Taxonomy of AISecOps Threat Modeling for Cloud Based Medical Chatbotscited by 0
  17. 2023Poisoning × Evasion: Symbiotic Adversarial Robustness for Graph Neural Networkscited by 0
  18. 2024From Latent to Lucid: Transforming Knowledge Graph Embeddings into Interpretable Structures with KGEPrismacited by 0
  19. 2024Performance Evaluation of Knowledge Graph Embedding Approaches under Non-adversarial Attackscited by 0
  20. 2024Explaining Graph Neural Networks for Node Similarity on Graphscited by 0
  21. 2024Extending TWIG: Zero-Shot Predictive Hyperparameter Selection for KGEs based on Graph Structurecited by 0
  22. 2025GRainsaCK: a Comprehensive Software Library for Benchmarking Explanations of Link Prediction Tasks on Knowledge Graphscited by 0
  23. 2025LLMAtKGE: Large Language Models as Explainable Attackers against Knowledge Graph Embeddingscited by 0
  24. 2026Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraintscited by 0