What question did this study set out to answer?

The aim is to present AnonShield, an efficient pseudonymization system for vulnerability data in CSIRT environments.

April 14, 2026Open Access

AnonShield: Scalable On-Premise Pseudonymization for CSIRT Vulnerability Data

Puntos clave

The aim is to present AnonShield, an efficient pseudonymization system for vulnerability data in CSIRT environments.
Developed a GPU-accelerated NER system for data processing
Implemented streaming processing and caching techniques
Configured schema-aware settings for optimal performance
Evaluated on datasets with over 70,000 records
Achieved processing time reduction from over 92 hours to under 10 minutes
Demonstrated a speedup of up to 738 times
Obtained up to 94.2% F1-score and 96.7% recall
Validated the feasibility of scalable pseudonymization without losing analytical utility

Resumen

We present AnonShield, a high-throughput, on-premise pseudonymization system that combines GPU-accelerated NER, streaming processing, caching, and schema-aware configuration. Evaluated on datasets up to 550 MB (70,951 records), AnonShield reduces processing time from over 92 hours to under 10 minutes (up to 738x speedup) while achieving up to 94.2% F1-score and 96.7% recall. Our results show that scalable pseudonymization of vulnerability data is feasible without sacrificing analytical utility, enabling compliant data sharing in operational CSIRT environments.

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Cite This Study

Kapelinski et al. (Mon,) studied this question.

synapsesocial.com/papers/69ddda22e195c95cdefd7b0a https://doi.org/https://doi.org/10.5281/zenodo.19538503

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