title: ÐÐ±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð²Ð½ÑÑÑÐµÐ½Ð½ÐµÐ³Ð¾ Ð½Ð°ÑÑÑÐ¸ÑÐµÐ»Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð·Ð°ÑÐ¸ÑÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð°Ð¿Ð¿Ð°ÑÐ°ÑÐ° Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹
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: Insider detection based on the encrypted traffic analysis using neural networks
Creators: name: ÐÐ·Ð¼Ð°Ð¹Ð»Ð¾Ð², ÐÐ»Ñ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: 2020
Subjects: Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÑ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð°Ð½Ð°Ð»Ð¸Ð· Ð·Ð°ÑÐ¸ÑÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ°
Ð²Ð½ÑÑÑÐµÐ½Ð½Ð¸Ð¹ Ð½Ð°ÑÑÑÐ¸ÑÐµÐ»Ñ
ÑÐ¸Ð½Ð³ÐµÑÐ¿ÑÐ¸Ð½Ñ
cybersecurity
machine learning
artificial neural networks
encrypted traffic analysis
insider
fingerprint

description: ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð² Ðº Ð°Ð½Ð°Ð»Ð¸Ð·Ñ Ð·Ð°ÑÐ¸ÑÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ° Ð¸ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ Ð¼ÐµÑÐ¾Ð´Ð° Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð½ÑÑ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð². ÐÐ°Ð´Ð°ÑÐ¸, ÐºÐ¾ÑÐ¾ÑÑÐµ ÑÐµÑÐ°Ð»Ð¸ÑÑ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: 1. Ð°Ð½Ð°Ð»Ð¸Ð· Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐµÐ¹ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÐ¸ Ð² ÑÐ¸ÑÑÐ¾Ð²Ð¾Ð¼ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´ÑÑÐ²Ðµ; 2. Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð² Ðº Ð°Ð½Ð°Ð»Ð¸Ð·Ñ Ð·Ð°ÑÐ¸ÑÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ°; 3. Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐµÐ¹ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸; 4. ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼ÐµÑÐ¾Ð´Ð° Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð·Ð°ÑÐ¸ÑÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ°; 5. ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ°Ð»ÑÐ½Ð°Ñ Ð¾ÑÐµÐ½ÐºÐ° ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð³Ð¾ Ð¼ÐµÑÐ¾Ð´Ð°. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼Ð½Ð¾Ð³Ð¾ÑÐ»Ð¾Ð¹Ð½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¿ÑÑÐ¼Ð¾Ð³Ð¾ ÑÐ°ÑÐ¿ÑÐ¾ÑÑÑÐ°Ð½ÐµÐ½Ð¸Ñ. Ð­ÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ°Ð»ÑÐ½Ð¾Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð¾ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð³Ð¾ Ð¼ÐµÑÐ¾Ð´Ð°.
description: The given work is devoted to studying of existing approaches to the analysis of encrypted traffic and the development of a neural network method for analyzing network traffic based on the studied approaches. The research set the following goals: 1. studying of the information security features in the digital production; 2. studying of existing approaches to the encrypted traffic analysis; 3. studying of machine learning methods to solve the classification problem; 4. development of a neural network method of encrypted traffic analysis; 5. experimental evaluation of the efficiency of the developed method. The study resulted into multilayer neural network based classifier building. Experimental research showed the effectiveness of the developed method.