WEBSITE ANALYSIS SOFTWARE DEVELOPMENT FOR THE LEAKAGE OF PERSONAL DATA

Purtov Daniil Vladimirovich, Purtov Vladimir Sergeevich, Shmitko Kirill Andreevich, Rusakov Aleksej Mixajlovich, Melnikov Aleksey Olegovich, Filatov Vyacheslav Valerievich

This article presents a study on developing a software tool, Web-PD-Scanner, which aims to analyze web pages in HTML format to detect potential personal data leakage. The article provides an overview of modern software tools for parsing web resources, as well as a review of HTML-page parsing technologies and their limitations. The relevance of the proposed study is substantiated, and the object, subject of research, scope, and limitations of the software are defined. The main tasks to be performed by the software are formulated, and various mathematical methods, algorithms, and software tools that can be used to develop the Web-PD-Scanner software are identified. The article concludes that a hybrid approach that combines rule-based algorithms and machine learning is the most effective solution for detecting leaks of personal data on websites. The next stage of the research involves defining a model for storing aggregated personal data and selecting specific methods and algorithms for developing the Web-PD-Scanner software. This study provides valuable insights for researchers and practitioners interested in developing software tools for analyzing web pages for personal data leakage.

Keywords:web scraping, data mining, HTML parsing, personal data protection, software development