title: ÐÐ½Ð°Ð»Ð¸Ð· Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ° Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸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: Network traffic security analysis by machine learning methods
Creators: name: ÐÑÑÐ¼Ð°Ð¼ÐµÐ´Ð¾Ð²Ð°, Ð¥Ð°Ð´Ð¸Ñ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: ÑÐ·ÑÐº
Ð²ÐµÐºÐ°
ÑÐµÑÐµÐ²Ð¾Ð¹ ÑÑÐ°ÑÐ¸Ðº
Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑÑÐ°Ð»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
ÑÐµÐ³ÑÐµÑÑÐ¸Ñ
java language
weka
network traffic
data mining
classification
regression

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÐ½Ð°Ð»Ð¸Ð· Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ° Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸ÑÂ». ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð°Ð½Ð°Ð»Ð¸Ð·Ñ Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ° Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, ÐºÐ¾ÑÐ¾ÑÑÐ¹ Ð±ÑÐ´ÐµÑ Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸ÑÑÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¿Ð°ÐºÐµÑÐ° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼ WEKA. ÐÐ»Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð±ÑÐ´ÐµÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÑÑÑ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ, ÑÐ¾ÑÑÐ¾ÑÑÐ¸Ð¹ Ð¸Ð· Ð¿ÑÑÐ¸ ÑÐ°Ð¹Ð»Ð¾Ð² Ñ Ð¿Ð¾Ð´ÑÐ¾Ð±Ð½Ð¾Ð¹ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸ÐµÐ¹ Ð¾ ÑÐµÑÐµÐ²Ð¾Ð¼ ÑÑÐ°ÑÐ¸ÐºÐµ. ÐÐ°Ð´Ð°ÑÐ¸, ÐºÐ¾ÑÐ¾ÑÑÐµ ÑÐµÑÐ°Ð»Ð¸ÑÑ Ð² ÑÐ¾Ð´Ðµ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ñ ÑÐ°Ð±Ð¾ÑÑ: 1. ÐÐ·ÑÑÐµÐ½Ð¸Ðµ Ð¿ÑÐµÐ´Ð¼ÐµÑÐ½Ð¾Ð¹ Ð¾Ð±Ð»Ð°ÑÑÐ¸; 2. ÐÐ·ÑÑÐµÐ½Ð¸Ðµ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÑ Ð·Ð°Ð´Ð°Ñ Ð¸ ÑÑÐ°Ð¿Ð¾Ð² Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑÑÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð´Ð°Ð½Ð½ÑÑ; 3. ÐÐ·ÑÑÐµÐ½Ð¸Ðµ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ, Ð²Ð·ÑÑÐ¾Ð³Ð¾ Ð´Ð»Ñ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð°; 4. ÐÐ·ÑÑÐµÐ½Ð¸Ðµ Ð¿Ð°ÐºÐµÑÐ° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼ WEKA; 5. ÐÐ±ÑÑÐµÐ½Ð¸Ðµ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ°; 6. ÐÑÐ±Ð¾Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸, Ð¿Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÑÑÐµÐ¹ Ð½Ð°Ð¸Ð»ÑÑÑÐ¸Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ. ÐÐ»Ñ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ° Ð±ÑÐ» Ð²ÑÐ±ÑÐ°Ð½ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ, Ð²Ð·ÑÑÑÐ¹ Ñ ÑÐ°Ð¹ÑÐ° ÐºÐ°Ð½Ð°Ð´ÑÐºÐ¾Ð³Ð¾ Ð£Ð½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑÐ° New Brunswick. ÐÐ°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ Ð²ÐºÐ»ÑÑÐ°ÐµÑ Ð´Ð°Ð½Ð½ÑÐµ Ð¾ Ð·Ð°Ð¿ÑÐ¾ÑÐ°Ñ Ð¿Ð¾ Ð¿ÑÐ¾ÑÐ¾ÐºÐ¾Ð»Ñ DoH Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¿ÑÑÐ¸ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð±ÑÐ°ÑÐ·ÐµÑÐ¾Ð² Ð¸ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ¾Ð². ÐÐ°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ ÑÐ¾Ð´ÐµÑÐ¶Ð¸Ñ Ð¿ÑÑÑ ÑÐ°Ð¹Ð»Ð¾Ð² Ñ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸ÐµÐ¹ Ð¾ ÑÐµÑÐµÐ²Ð¾Ð¼ ÑÑÐ°ÑÐ¸ÐºÐµ. ÐÐ°Ð¶Ð´ÑÐ¹ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ ÑÐ¾Ð´ÐµÑÐ¶Ð¸Ñ 35 Ð°ÑÑÐ¸Ð±ÑÑÐ¾Ð² (SourceIP, DestinationIP, SourcePort, DestinationPort, TimeStamp, Duration Ð¸ Ñ.Ð´.).
description: The subject of graduate qualification work: "Analysis of network traffic security by machine learning methods". The given work is devoted to the analysis of the security of network traffic using machine learning methods, which will be carried out using the WEKA software package. For analysis, there will be a dataset consisting of five files with detailed information about network traffic. The research set the following goals: 1. Study of the subject area. 2. Study of main tasks and stages of data mining. 3. Study of the dataset taken for analysis. 4. Study of the WEKA software package; 5. Training models for classifying network traffic; 6. Choice of the model showing the best results. The dataset taken from the website of the Canadian University of New Brunswick was selected to analyze the security of network traffic. The dataset includes DoH request data using five different browsers and tools. The dataset contains five files with information about network traffic. Each dataset contains 35 attributes (SourceIP, DestinationIP, SourcePort, DestinationPort, TimeStamp, Duration, etc.).