title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð½ÑÐ¸ÑÐ¿Ð°Ð¼-ÑÐ´ÑÐ° Ð´Ð»Ñ Ð¿Ð¾ÑÑÐ¾Ð²ÑÑ ÑÐµÑÐ²Ð¸ÑÐ¾Ð²
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Development of an antispam core for mail services
Creators: name: ÐÑÑÐ»Ð¾Ð², Ð¤ÐµÐ´Ð¾Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð°Ð½ÑÐ¸ÑÐ¿Ð°Ð¼
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
ÑÑÑÐ½ÑÐµ-ÑÐ¿Ð¸ÑÐºÐ¸
C++
antispam
machine learning
classification
black lists

description: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° ÑÑÐµÐ´ÑÑÐ² Ð·Ð°ÑÐ¸ÑÑ Ð¾Ñ ÑÐ¿Ð°Ð¼Ð° Ð°ÐºÑÑÐ°Ð»ÑÐ½Ð°, Ð¿Ð¾ÑÐºÐ¾Ð»ÑÐºÑ ÑÐ¿Ð°Ð¼ Ð² ÑÐ»ÐµÐºÑÑÐ¾Ð½Ð½ÑÑ Ð¿Ð¸ÑÑÐ¼Ð°Ñ Ð¸ ÑÐ¾Ð¾Ð±ÑÐµÐ½Ð¸ÑÑ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÑÐµÑ ÑÐ¾Ð±Ð¾Ð¹ ÑÐµÑÑÐµÐ·Ð½ÑÑ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð´Ð»Ñ Ð¾ÑÐ´ÐµÐ»ÑÐ½ÑÑ Ð»Ð¸Ñ, Ð¿ÑÐµÐ´Ð¿ÑÐ¸ÑÑÐ¸Ð¹ Ð¸ Ð¾ÑÐ³Ð°Ð½Ð¸Ð·Ð°ÑÐ¸Ð¹. Ð­ÑÐ¸ Ð½ÐµÐ¶ÐµÐ»Ð°ÑÐµÐ»ÑÐ½ÑÐµ ÑÐ¾-Ð¾Ð±ÑÐµÐ½Ð¸Ñ Ð¼Ð¾Ð³ÑÑ Ð¿ÐµÑÐµÐ³ÑÑÐ¶Ð°ÑÑ Ð¿Ð¾ÑÑÐ¾Ð²ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ, Ð·Ð°Ð¼ÐµÐ´Ð»ÑÑÑ ÑÐµÑÐµÐ²Ð¾Ð¹ ÑÑÐ°ÑÐ¸Ðº Ð¸ Ð´Ð°Ð¶Ðµ ÑÐ°ÑÐ¿ÑÐ¾ÑÑÑÐ°Ð½ÑÑÑ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÐµ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ Ð¸ Ð²Ð¸ÑÑÑÑ. Ð ÑÐ°Ð¼ÐºÐ°Ñ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð½ Ð¿ÑÐ¾ÑÐµÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð°Ð½ÑÐ¸ÑÐ¿Ð°Ð¼-ÑÐ´ÑÐ° Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¿Ð¸ÑÐµÐ¼ Ð½Ð° ÑÐ¿Ð°Ð¼ Ð¸ Ð½Ðµ ÑÐ¿Ð°Ð¼. ÐÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, ÑÐ°ÐºÐ¾Ð³Ð¾ ÐºÐ°Ðº Ð½Ð°Ð¸Ð²Ð½Ð°Ñ ÐÐ°Ð¹ÐµÑÐ¾Ð²ÑÐºÐ°Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ, Ð¼ÐµÑÐ¾Ð´Ð° Ð¾Ð±ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ ÑÐµÑÐ½ÑÑ ÑÐ¿Ð¸ÑÐºÐ¾Ð² Ð´Ð»Ñ IP Ð°Ð´ÑÐµÑÐ¾Ð², Ð½Ð¾Ð¼ÐµÑÐ¾Ð² ÑÐµÐ»ÐµÑÐ¾Ð½Ð¾Ð² Ð¸Ð· ÑÐµÐºÑÑÐ° Ð¿Ð¸ÑÑÐ¼Ð°, email Ð°Ð´ÑÐµÑÐ¾Ð² Ð¾ÑÐ¿ÑÐ°Ð²Ð¸ÑÐµÐ»ÐµÐ¹, ÑÑÑÐ»Ð¾Ðº Ð¸Ð· Ð¿Ð¸ÑÑÐ¼Ð°. Ð ÑÐ°Ð¼ÐºÐ°Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ ÑÐ°ÐºÐ¸Ðµ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¸ Ð¸ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÑ: C++ 17, Cmake, conan, git, Ms Visual Studio. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð¾ ÑÐ¾Ð·Ð´Ð°Ð½Ð¾ Ð°Ð½ÑÐ¸ÑÐ¿Ð°Ð¼-ÑÐ´ÑÐ¾, Ð² ÐºÐ¾ÑÐ¾ÑÐ¾Ð¼ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ñ Ð¼ÐµÑÐ¾Ð´Ñ ÐÐ°Ð¹ÐµÑÐ¾Ð²ÑÐºÐ¾Ð¹ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸ Ð¸ ÑÐµÑÐ½ÑÐµ ÑÐ¿Ð¸ÑÐºÐ¸, Ð¿ÑÐ¸ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ Ð½Ð° Ð±Ð¾Ð»ÑÑÐ¾Ð¼ Ð½Ð°Ð±Ð¾ÑÐµ Ð¿Ð¸ÑÐµÐ¼ Ð±ÑÐ»Ð¾ ÑÑÑÐ°Ð½Ð¾Ð²Ð»ÐµÐ½Ð¾, ÑÑÐ¾ ÐºÐ°Ð¶Ð´Ð¾Ðµ Ð´ÐµÑÑÑÐ¾Ðµ Ð¿Ð¸ÑÑÐ¼Ð¾ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÑÐµÑÑÑ Ð½ÐµÐ¿ÑÐ°Ð²Ð¸Ð»ÑÐ½Ð¾, ÑÐ¾ ÐµÑÑÑ Ð°Ð½ÑÐ¸ÑÐ¿Ð°Ð¼-ÑÐ´ÑÐ¾ Ð²ÑÐ´Ð°ÐµÑ Ð¿ÑÐ°Ð²Ð¸Ð»ÑÐ½ÑÐ¹ ÑÐµÐ·ÑÐ»ÑÑÐ°Ñ Ð² 90% ÑÐ»ÑÑÐ°ÐµÐ², ÑÑÐ¾ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ¾ÑÐ¾ÑÐ¸Ð¼ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð¼ Ð´Ð»Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼ Ð¸Ð· ÑÑÐµÑÑ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¿Ð¸ÑÐµÐ¼.
description: Developing spam protection tools is relevant because spam in emails and mesages is a serious problem for individuals, businesses and organizations. These unwanted messages can overload email systems, slow down network traffic, and even spread malware and viruses. This paper shows the process of developing an anti-spam kernel to classify emails into spam and non-spam. The classification is done using machine learning such as naive Bayesian classification, blacklist declaration method for IP addresses, phone numbers from the letter text, sender email addresses, links from the letter. The technologies and tools used in the development included: C++ 17, Cmake, conan, git, Ms Visual Studio. As the result of this work the anti-spam-core was created in which meth-ods of Bayesian filtering and blacklists were realized. While testing with a large set of letters it was found that every tenth letter is defined incorrectly, that is, the anti-spam-core gives a correct result in 90% of cases and this is a good result for programs from the field of e-mail classification.