AnonLFI 2.0: Extensible Architecture for PII Pseudonymization in CSIRTs with OCR and Technical Recognizers - Kapelinski, Cristhian; Lautert, Douglas; Machado, Beatriz; Kreutz, Diego (Anais da Escola Regional de Redes de Computadores (ERRC); 2025: Anais da XXII Escola Regional de Redes de ComputadoresDO - 10.5753/errc.2025.17784, 2025)
This work presents AnonLFI 2.0, a modular pseudonymization framework for CSIRTs that employs HMAC–SHA256 to generate strong and reversible pseudonyms, preserves the structural integrity of XML and JSON documents, and integrates OCR as well as specialized technical recognizers for PII and security–related artifacts. In two case studies involving OCR applied to PDF files and the pseudonymization of OpenVAS XML reports, the system achieved 100% precision and F1 scores of 76.5% and 92.13%, demonstrating its effectiveness for the secure preparation of complex cybersecurity datasets.