Risk management for General Data Protection Regulation
DOI:
https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1286Keywords:
Fuzzy Logic, Risk Assessment, Law EnforcementAbstract
Objective: To develop a new model for assessing privacy risks related to the General Data Protection Law (LGPD) in the digital health environment. Methods: Construction of a model based on Fuzzy Logic, considering best practices from the technical standards of the Brazilian Association of Technical Standards (ABNT) and the International Organization for Standardization (ISO) to incorporate uncertainty in the evaluation process as well as the explainability of results from the identification of variables relevant to the concept of risk for LGPD. Results: The new model showed good results compared to other models, and, differently, included the explanation of the obtained results. Conclusion: The proposed system using the model titled Fuzzy-LGPD for Risk Management in Digital Health presented very promising results, allowing the identification of risks in the evaluated case studies.
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