Authors: Igor Kotenko; Andrey Chechulin; Dmitry Komashinsky
Addresses: Laboratory of Computer Security Problems, St. Petersburg Institute for Informatics and Automation, 39, 14th Liniya, Saint-Petersburg, Russia ' Laboratory of Computer Security Problems, St. Petersburg Institute for Informatics and Automation, 39, 14th Liniya, Saint-Petersburg, Russia ' F-Secure Corporation, Tammasaarenkatu 7, PL 24, 00181 Helsinki, Finland
Abstract: The paper outlines a framework for automated categorisation of web pages to protect against inappropriate content. The paper contains the framework overview, analysis of state-of-the-art, description of the developed prototype and its evaluation based on series of experiments. Several sources are used for the categorisation, namely text, HTML tags and URL addresses. During the categorisation, this data and other information are analysed using machine learning and data mining methods. Finally, the evaluation of the categorisation quality is performed. The categorisation system developed as a result of this work are planned to be partially implemented in F-Secure Corporation in mass production systems performing analysis of web content.
Keywords: web pages; categorisation; classification; inappropriate content; data mining; text analysis; HTML analysis; URL addresses; user protection; internet; machine learning; web content analysis.
International Journal of Internet Protocol Technology, 2017 Vol.10 No.1, pp.61 - 71
Available online: 13 Mar 2017 *Full-text access for editors Access for subscribers Purchase this article Comment on this article