title: ÐÐ±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð²ÐµÐ±-Ð°ÑÐ°Ðº Ð² Ð¾Ð±Ð»Ð°ÑÐ½ÑÑ ÑÐµÑÐ²Ð¸Ñ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: Detection of web attacks in cloud services
Creators: name: Ð¡Ð°ÑÐ¸ÑÐ»Ð¸Ð½Ð°, ÐÐ¸Ð°Ð½Ð°
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: Ð¾Ð±Ð»Ð°ÑÐ½ÑÐµ ÑÐµÑÐ²Ð¸ÑÑ
Ð²ÐµÐ±-Ð°ÑÐ°ÐºÐ¸
sql-injection
xss
brute force
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
random forest
cloud services
web attacks
sql injection
machine learning

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 Ð²ÐµÐ±-Ð°ÑÐ°Ðº Ð² Ð¾Ð±Ð»Ð°ÑÐ½ÑÑ ÑÐµÑÐ²Ð¸ÑÐ°Ñ. ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÐµÑÑÑ Ð²ÑÐ±Ð¾Ñ Ð¾Ð¿ÑÐ¸Ð¼Ð°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÐµÐ±-Ð°ÑÐ°Ðº Ñ ÑÐ¾ÑÐ½Ð¾ÑÑÑÑ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ Ð°ÑÐ°ÐºÐ¸ Ð²ÑÑÐµ, ÑÐµÐ¼ Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ ÑÐ¸ÑÑÐµÐ¼ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð°ÑÐ°Ðº (Ð¡ÐÐ). 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· ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¹ Ð² Ð¾Ð±Ð»Ð°ÑÑÐ¸ Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÐ¸ Ð¾Ð±Ð»Ð°ÑÐ½ÑÑ ÑÐµÑÐ²Ð¸ÑÐ¾Ð²; 2. ÐÑÐ±ÑÐ°ÑÑ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ Ð¸ ÑÐ´ÐµÐ»Ð°ÑÑ Ð¿ÑÐµÐ´Ð²Ð°ÑÐ¸ÑÐµÐ»ÑÐ½ÑÑ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÑ; 3. ÐÑÐ¾Ð²ÐµÑÑÐ¸ Ð¾ÑÐµÐ½ÐºÑ Ð¸ Ð¾ÑÐ±Ð¾Ñ Ð·Ð½Ð°ÑÐ¸Ð¼ÑÑ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ; 4. ÐÑÐ±ÑÐ°ÑÑ, Ð½Ð°ÑÑÑÐ¾Ð¸ÑÑ Ð¸ Ð¾Ð±ÑÑÐ¸ÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ; 5. ÐÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð½ÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð². Â  Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ» Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ CIC-IDS2017, ÐµÐ³Ð¾ ÑÑÑÑÐºÑÑÑÐ° Ð¸ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¸. ÐÑÐ»Ð¸ Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ñ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð² Ð¾Ð±Ð»Ð°ÑÑÐ¸ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÐµÐ±-Ð°ÑÐ°Ðº. Â  Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð¾ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð¾ ÑÑÐ¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ Ð¿ÑÐ¾Ð²ÐµÐ´ÑÐ½ Ð¸Ñ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·. ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÐµÐ±-Ð°ÑÐ°Ðº Ð² Ð¾Ð±Ð»Ð°ÑÐ½ÑÑ ÑÐµÑÐ²Ð¸ÑÐ°Ñ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ð¹ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ Random Forest. ÐÑÐ»Ð° Ð¿ÑÐ¾Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð° ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ ÑÑÐµÐ´ÑÑÐ²Ð° Ð¿Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ñ Ñ Ð´ÑÑÐ³Ð¸Ð¼Ð¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ Ð¿Ð¾Ð¿ÑÐ»ÑÑÐ½Ð¾Ð¹ Ð¡ÐÐ, Snort. ÐÑÐ» ÑÐ´ÐµÐ»Ð°Ð½ Ð²ÑÐ²Ð¾Ð´, ÑÑÐ¾ Ð¡ÐÐ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸Ð¼ÐµÑÑ Ð±Ð¾Ð»ÑÑÑÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð°ÑÐ°Ðº Ð¸ Ð¸Ñ ÑÐ»ÐµÐ´ÑÐµÑ Ð²Ð½ÐµÐ´ÑÑÑÑ Ð² ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ðµ ÑÐµÑ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 Ð²Ð½ÐµÐ´ÑÐµÐ½Ð¸Ñ Ð² ÑÐ¸ÑÑÐµÐ¼Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð°ÑÐ°Ðº Ð¾Ð±Ð»Ð°ÑÐ½ÑÑ ÑÐµÑÐ²Ð¸ÑÐ¾Ð².
description: The aim of the work is to improve the quality of web attack detection in cloud services. The subject of the study is the choice of an optimal machine learning algorithm for detecting web attacks with an attack detection accuracy higher than that of existing attack detection systems (SOA). Tasks to be solved during the research: 1. To analyze modern research in the field of security of cloud services; 2. Select the data set and do the preprocessing; 3. Evaluate and select significant features of the data set; 4. Select, configure and train machine learning algorithms; 5. Analyze the results of the implemented algorithms. In the course of the work, the CIC-IDS2017 dataset, its structure and features were investigated. Modern research in the field of web attack detection was analyzed. As a result of the work, three machine learning algorithms were implemented and their comparative analysis was carried out. Based on the results of the analysis, a software prototype for detecting web attacks in cloud services using the Random Forest algorithm has been developed. The effectiveness of the tool was demonstrated in comparison with other machine learning algorithms and the popular SOA, Snort. It was concluded that machine learning-based SOAS are more effective at detecting attacks and should be implemented into existing solutions. The results obtained can be used to implement cloud services into attack detection systems.