A Program for Depersonalizing Personal Data in Legal Documents by Extracting Named Entities Using Artificial Intelligence Methods

Student: Kirill Grafov

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Cybersecurity (Master)

Year of Graduation: 2024

This paper deals with the problem of depersonalizing digital data in legal documents using artificial intelligence methods. The relevance of the task is substantiated during the period of need to comply with the requirements for protecting digital data and ensuring information confidentiality. The developed program is a tool based on methods for extracting named entities from text using machine learning algorithms. The program is implemented in the Python programming language. In summary, the rapid work is a comprehensive study aimed at developing software tools for anonymizing scientific data in legal documents using artificial intelligence methods. The work contains 69 pages, 16 figures, 12 tables, 21 sources, 2 appendices.

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