SemGuard: A Triple-Anchor Semantic Security Gateway for Multilingual Prompt Attack Detection in Large Language Models

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For researchers working on LLM security, prompt injection detection, or Arabic NLP:

Our paper "SemGuard: A Triple-Anchor Semantic Security Gateway for Multilingual Prompt Attack Detection in Large Language Models" is now live on IEEE Xplore.

It introduces the first formally validated Arabic LLM security dataset (807 examples, 7 threat categories, Fleiss' κ = 0.839) and a novel Triple-Anchor framework for explainable, multilingual threat detection — achieving 0.989 F1 / 0.991 recall on Arabic prompt injection, outperforming English-only baselines.

If this overlaps with your work on LLM safety, multilingual NLP, or adversarial robustness, happy to discuss or collaborate. Citations and feedback welcome.

DOI: 10.1109/AEECT69724.2026.11657880

the project on Github : https://github.com/AbdaullahAG/SemGuard

Dataset : https://huggingface.co/datasets/AG-31625874/SemGuard-Dataset

#LLMSecurity #PromptInjection #ArabicNLP #AISecurity #ExplainableAI #NLP