title: ÐÑÐµÐ½ÐºÐ° ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾ÑÑÐ¸ Ð°Ð½ÑÐ¸Ð²Ð¸ÑÑÑÐ½ÑÑ ÑÑÐµÐ´ÑÑÐ² Ðº ÑÐ¾ÑÑÑÐ·Ð°ÑÐµÐ»ÑÐ½ÑÐ¼ Ð°ÑÐ°ÐºÐ°Ð¼
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸ÑÑÐ°
titleType: Subtitle
title: Evaluation the robustness of antivirus tools to adversarial attacks
Creators: name: Ð Ð¾ÑÐ¸Ð½, Ð Ð¾Ð¼Ð°Ð½
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Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ
ÑÐ¾ÑÑÑÐ·Ð°ÑÐµÐ»ÑÐ½ÑÐµ Ð°ÑÐ°ÐºÐ¸
Ð°Ð½ÑÐ¸Ð²Ð¸ÑÑÑÐ½ÑÐµ ÑÑÐµÐ´ÑÑÐ²Ð°
adversarial attacks
antivirus software

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description: The purpose of the study is to evaluate the robustness of antivirus tools that use machine learning to adversarial attacks, and to develop methods to improve their robustness. The subject of the work is methods and algorithms of adversarial attacks and improving of robustness to them machine learning models. The research set the following goals: 1) researching of the use of machine learning in antivirus tools; 2) studying of existing methods for generating adversarial examples from malware source files; 3) development of a method for generating adversarial samples for antivirus testing; 4) development of a tool that creates adversarial samples and evaluating the robustness of antivirus to their use; 5) suggesting ways to improve the robustness of antivirus tools to adversarial attacks. In the course of the work, existing methods for generating adversarial samples from malware source files were considered, tools for generating adversarial samples were created, and experiments were carried out to assess the stability of antivirus tools. As a result, methods for improving antivirus analysis against adversarial attacks were proposed and experimentally evaluated. The results obtained can be used by antivirus labs and vendors that use machine learning for their tools.