Analysis of machine learning methods for filtering spam messages in email services
Ganiev Salim KarimovichInformation Security Provision, professor Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, UzbekistanKhamidov Sherzod Jaloldin ugliInformation Security Provision, professor Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, UzbekistanOlimov Iskandar SalimbayevichInformation Security Provision, professor Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, Uzbekistan
2020 International Conference on Information Science and Communications Technologies (ICISCT)conference2020en
ABI
Abstract
In this paper describes the advantages and disadvantages of methods for detecting and protecting against spam messages in electronic mail services, considers the classification of spam messages and the Naive Bayes spam filter used to classify spam messages. The characteristics and effectiveness of spam filters based on machine learning methods are analyzed.