title: ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð° Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ Ð±ÑÑÑÐ¸Ð½Ð³Ð° Ð² Ð·Ð°Ð´Ð°ÑÐµ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ ÑÐµÑÐµÐ²ÑÑ Ð°ÑÐ°Ðº
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: Research of the method of gradient boosting in the task of detection of network attacks
Creators: name: ÐÐ¾ÑÐ½ÑÐºÐ¾Ð²Ð°, Ð®Ð»Ð¸Ñ
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: 2024
Subjects: Ð°Ð½ÑÐ°Ð¼Ð±Ð»ÐµÐ²ÑÐ¹ Ð¿Ð¾Ð´Ñ Ð¾Ð´
Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½Ð¾Ðµ ÑÑÐ¸Ð»ÐµÐ½Ð¸Ðµ
ÑÐ¸ÑÑÐµÐ¼Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐ¾ÑÐ¶ÐµÐ½Ð¸Ñ
ÑÐ»ÑÑÐ°Ð¹Ð½ÑÐ¹ Ð»ÐµÑ
Ð°ÑÐ°ÐºÐ¸ Ð² ÑÐµÑÐµÐ²Ð¾Ð¼ ÑÑÐ°ÑÐ¸ÐºÐµ
ensemble approach
gradient boosting algorithm
intrusion detection systems
random forest
attacks on network traffic

description: Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ðµ ÐºÐ°ÑÐµÑÑÐ²Ð° Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐ¾ÑÐ¶ÐµÐ½Ð¸Ð¹ Ð°Ð½ÑÐ°Ð¼Ð±Ð»ÐµÐ²ÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ ÑÑÐ¸Ð»ÐµÐ½Ð¸Ñ Ð² ÑÐµÑÐµÐ²Ð¾Ð¼ ÑÑÐ°ÑÐ¸ÐºÐµ. ÐÐ¾Ð´ ÐºÐ°ÑÐµÑÑÐ²Ð¾Ð¼ Ð¿Ð¾Ð½Ð¸Ð¼Ð°ÐµÑÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ ÐºÐ°Ð¶Ð´Ð¾Ð³Ð¾ ÑÐ¸Ð¿Ð° Ð°ÑÐ°Ðº. ÐÐ±ÑÐµÐºÑÐ¾Ð¼ Ð´Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÐµÑÑÑ ÑÑÐ°ÑÐ¸Ðº, Ð³ÐµÐ½ÐµÑÐ¸ÑÑÐµÐ¼ÑÐ¹ ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð°Ð¼Ð¸ Ð¸Ð½ÑÐµÑÐ½ÐµÑÐ° Ð²ÐµÑÐµÐ¹. ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð¼ÐµÑÐ¾Ð´Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð°ÑÐ°Ðº. ÐÐ°Ð´Ð°ÑÐ¸, ÑÐµÑÐ°ÐµÐ¼ÑÐµ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: 1. ÐÑÐ¾Ð²ÐµÑÑÐ¸ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¸ÑÑÐ»ÐµÐ´ÑÐµÐ¼Ð¾Ð³Ð¾ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ, ÐµÐ³Ð¾ ÑÐ°ÑÐ°ÐºÑÐµÑÐ¸ÑÑÐ¸Ðº Ð¸ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐµÐ¹. 2. ÐÑÐ¾Ð²ÐµÑÑÐ¸ Ð°Ð½Ð°Ð»Ð¸Ð· Ð°Ð½ÑÐ°Ð¼Ð±Ð»ÐµÐ²ÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¸ Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ ÑÑÐ¸Ð»ÐµÐ½Ð¸Ñ. 3. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°ÑÑ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ Ð±ÑÑÑÐ¸Ð½Ð³Ð°, ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÑÐ¸ÑÑÑÑÐ¸Ð¹ ÑÐµÑÐµÐ²ÑÐµ Ð°ÑÐ°ÐºÐ¸. 4. ÐÑÐ¾Ð²ÐµÑÑÐ¸ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÑ Ð¸ Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ» ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿, ÑÐµÑÐ°ÑÑÐ¸Ð¹ Ð·Ð°Ð´Ð°ÑÑ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ ÑÐµÑÐµÐ²ÑÑ Ð°ÑÐ°Ðº, Ð¸ Ð±ÑÐ»Ð° Ð¿ÑÐ¾Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð°Ñ ÐµÐ³Ð¾ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑ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 Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð¾ÑÐ½Ð¾Ð²Ñ Ð´Ð»Ñ Ð´Ð°Ð»ÑÐ½ÐµÐ¹ÑÐ¸Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¹ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÐµÐ¹ Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ ÑÑÐ¸Ð»ÐµÐ½Ð¸Ñ Ð² Ð·Ð°Ð´Ð°ÑÐµ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÑÐµÑÐµÐ²ÑÑ Ð°ÑÐ°Ðº.
description: The aim of the work is to improve the quality of intrusion detection of ensemble models using gradient boosting in network traffic. Quality is understood as the accuracy of detection of each type of attack. The object of this research is the traffic generated by Internet of Things devices. The subject of the study is attack detection methods. The objectives addressed in the research are: 1. To analyze the dataset under study, its characteristics and features. 2. To analyze the ensemble models and gradient boosting. 3. Develop a software prototype based on gradient boosting that classified network attacks. 4. Conduct experiments and analyze the classification results. As a result of this work, has been developed a software prototype that solves the problem of network attack detection and its effectiveness has been demonstrated. The obtained results can be used as a basis for further research into the possibilities of gradient amplification in the task of classifying network attacks.