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The article proposes a model that improves personal data protection through de-identification, suggesting new algorithms.
This article describes a solution for systematizing the approach to personal data protection using the method of de-identification in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing de-identification methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.
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Zarina Ildarovna Azizova (2026) studied this question.
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