title: Ð¡ÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð´Ð»Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð·Ð»Ð¾Ð½Ð°Ð¼ÐµÑÐµÐ½Ð½Ð¾Ð³Ð¾ DoH-ÑÑÐ°ÑÐ¸ÐºÐ°
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: Comparative analysis of classification methods for detecting malicious DoH traffic
Creators: name: ÐÐ¾Ð»Ð¾Ð¶ÐµÐ½ÑÐµÐ², ÐÐ°Ð½Ð¸Ð¸Ð»
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: 2022
Subjects: Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÐ¹ ÑÑÐ°ÑÐ¸Ðº
Ð°Ð½Ð°Ð»Ð¸Ð·
ÑÑÐµÐ´ÑÑÐ²Ð¾ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐ¾ÑÐ¶ÐµÐ½Ð¸Ð¹
DNS over HTTPS
malicious traffic
analysis
intrusion detection system
Godlua

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«Ð¡ÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð´Ð»Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð·Ð»Ð¾Ð½Ð°Ð¼ÐµÑÐµÐ½Ð½Ð¾Ð³Ð¾ DoH-ÑÑÐ°ÑÐ¸ÐºÐ°Â».Ð¦ÐµÐ»ÑÑ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ðµ ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸ Ð¸ Ð±ÑÑÑÑÐ¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ DOH-ÑÑÐ°ÑÐ¸ÐºÐ° Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð¼ÐµÑÐ¾Ð´Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¾Ð±Ð½Ð°ÑÑÐ¶Ð¸Ð²Ð°ÑÑÐ¸Ðµ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÐ¹ DoH-ÑÑÐ°ÑÐ¸Ðº. ÐÐ»Ñ Ð´Ð¾ÑÑÐ¸Ð¶ÐµÐ½Ð¸Ñ ÑÐºÐ°Ð·Ð°Ð½Ð½Ð¾Ð¹ ÑÐµÐ»Ð¸ Ð±ÑÐ»Ð¸ Ð¿Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ñ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð·Ð°Ð´Ð°ÑÐ¸:ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¸ DoH Ð´Ð»Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ.ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐ¸ ÑÐ°Ð±Ð¾ÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÐµÐ¼ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ.ÐÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ðµ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ Ð½Ð°Ð¸Ð±Ð¾Ð»ÐµÐµ Ð¿Ð¾Ð´ÑÐ¾Ð´ÑÑÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð´Ð»Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ DoH-ÑÑÐ°ÑÐ¸ÐºÐ°.ÐÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ ÑÐµÐ»ÐµÑÐ¾Ð¾Ð±ÑÐ°Ð·Ð½Ð¾ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð° Ð³Ð»Ð°Ð²Ð½ÑÑ ÐºÐ¾Ð¼Ð¿Ð¾Ð½ÐµÐ½Ñ Ð² Ð·Ð°Ð´Ð°ÑÐµ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ doh-ÑÑÐ°ÑÐ¸ÐºÐ°.Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð° Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð° ÑÐ°Ð±Ð¾ÑÐ° DNS Ð¸ DNS over HTTPS. ÐÑÐ»Ð¸ Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ñ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÐµ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ðµ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ñ DNS over HTTPS.Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ» Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ DoH-ÑÑÐ°ÑÐ¸ÐºÐ°, Ð±ÑÐ»Ð¾ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¾ Ð±ÑÑÑÑÐ¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ.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 Ð´Ð»Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÑÐµÐ´ÑÑÐ²Ð° Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐ¾ÑÐ¶ÐµÐ½Ð¸Ð¹ ÑÐµÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð²ÑÐµÐ¼ÐµÐ½Ð¸.
description: The topic of the graduate qualification work is Â« Comparative analysis of classification methods for detecting malicious DoH trafficÂ».The purpose of the study is improving the efficiency of detecting malicious DOH traffic using machine learning methods. The subject of the work is machine learning methods that detect malicious DoH traffic. The research set the following goals:Exploring DoH technology for machine learning applications.Studying of the features of the work of the used machine learning methods.Carry out a comparative analysis of machine learning methods to determine the most suitable methods for detecting malicious DoH traffic.Analyze the feasibility of using the principal component method in the problem of detecting malicious doh traffic.Increasing efficiency by using the principal components method to reduce the dimension of the features of the sample used during comparative analysis.During the work, the work of DNS and DNS over HTTPS was investigated. Modern malware using DNS over HTTPS technology was analyzed.As a result of the work, a comparative analysis of machine learning methods for detecting malicious DoH traffic was carried out, and the efficiency of detection methods was increased.The results obtained can be used to implement a real-time intrusion detection system.