title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð² Ð¸ÑÐ¿Ð¾Ð»Ð½ÑÐµÐ¼ÑÑ ÑÐ°Ð¹Ð»Ð°Ñ
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: Applying machine learning techniques to detect malware in executable files
Creators: name: ÐÐ¾Ð»ÐºÐ¾Ð²ÑÐºÐ¸Ð¹, ÐÐ°ÐºÑÐ¸Ð¼
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: Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ
ÑÑÐ°ÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð°Ð½Ð°Ð»Ð¸Ð·
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð³Ð»ÑÐ±Ð¾ÐºÐ¸Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð°Ð½Ð°Ð»Ð¸Ð· Ð´Ð¸Ð·Ð°ÑÐµÐ¼Ð±Ð»Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ ÐºÐ¾Ð´Ð°
detection of malicious software
static analysis
machine learning
deep neural networks
disassembled code analysis

description: Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¿Ð¾Ð´ÑÐ¾Ð´Ð° Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð² Ð¸ÑÐ¿Ð¾Ð»Ð½ÑÐµÐ¼ÑÑ ÑÐ°Ð¹Ð»Ð°Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÑÐ°ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½Ð° Ð¿ÑÐ¸Ð¼ÐµÑÐµ Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ Windows. ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ. ÐÐ°Ð´Ð°ÑÐ¸, ÑÐµÑÐ°ÐµÐ¼ÑÐµ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: â Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ ÑÑÑÑÐºÑÑÑÑ Ð¸ÑÐ¿Ð¾Ð»Ð½ÑÐµÐ¼ÑÑ ÑÐ°Ð¹Ð»Ð¾Ð² Ð¸ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÐµ ÐºÐ»Ð°ÑÑÑ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ ÐÐ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ Windows; â Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÑ Ð¼ÐµÑÐ¾Ð´Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð² Ð¸ÑÐ¿Ð¾Ð»Ð½ÑÐµÐ¼ÑÑ ÑÐ°Ð¹Ð»Ð°Ñ; â ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°ÑÑ Ð¼ÐµÑÐ¾Ð´ Ðº Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð² Ð¸ÑÐ¿Ð¾Ð»Ð½ÑÐµÐ¼ÑÑ ÑÐ°Ð¹Ð»Ð°Ñ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ; â ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°ÑÑ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ ÑÑÐµÐ´ÑÑÐ²Ð° Ð´Ð»Ñ Ð¾ÑÑÑÐµÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÑÑÐ°Ð½Ð°Ð²Ð»Ð¸Ð²Ð°ÐµÐ¼Ð¾Ð³Ð¾ ÐÐ, ÑÐµÐ°Ð»Ð¸Ð·ÑÑÑÐµÐµ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½ÑÐ¹ Ð¼ÐµÑÐ¾Ð´; â Ð¿ÑÐ¾Ð²ÐµÑÑÐ¸ Ð¾ÑÐµÐ½ÐºÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð³Ð¾ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿Ð° Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ð¼Ð¸ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸ÑÐ¼Ð¸. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ» Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½ Ð¸ Ð¿ÑÐ¾ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½ Ð¼ÐµÑÐ¾Ð´ Ð´Ð»Ñ Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÑ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼ Ð¿ÑÑÐµÐ¼ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð°ÑÑÐµÐ¼Ð±Ð»ÐµÑÐ½Ð¾Ð³Ð¾ ÐºÐ¾Ð´Ð°, Ð° ÑÐ°ÐºÐ¶Ðµ Ð½Ð° ÐµÐ³Ð¾ Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ ÑÑÐµÐ´ÑÑÐ²Ð° Ð´Ð»Ñ Ð¾ÑÑÑÐµÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÑÑÐ°Ð½Ð°Ð²Ð»Ð¸Ð²Ð°ÐµÐ¼Ð¾Ð³Ð¾ ÐÐ, Ð±ÑÐ»Ð° Ð¿ÑÐ¾Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð° ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð°. ÐÐ¾Ð»ÑÑÐµÐ½Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¼Ð¾Ð³ÑÑ Ð±ÑÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð¾ÑÐ½Ð¾Ð²Ñ Ð´Ð»Ñ Ð¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐ¸ÑÑÐµÐ¼ ÑÑÐ°ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ.
description: The aim of the work is to develop an approach to detect malware in executable files based on static analysis using machine learning on the example of the Windows operating system. The subject of the research is modern methods of classifying malware using machine learning. Tasks to be solved during the research: â analyze the structure of executable files and major classes of malware based on the Windows operating system; â investigate methods to detect malware in executable files; â develop a method to detect malware in executable files using machine learning; â develop a prototype software tool for analyzing installed software that implements the developed method; â evaluate the effectiveness of the developed prototype and compare it with existing implementations; â the classes of malware and the structure of executable files were analyzed in the course of the work. The approaches to the construction of malware in executable files were reviewed and systematized. As the result the method of malware detection by analyzing the assembler code was proposed and tested; using this method the prototype of a software tool for analyzing the installed software was developed, and the effectiveness of the method was demonstrated. The results can be used as a basis for designing static malware analysis systems.