title: ÐÐ±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð°ÑÐ°Ðº Ð½Ð° "ÑÐ¼Ð½ÑÐµ Ð·Ð´Ð°Ð½Ð¸Ñ" Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² 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° ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸ÑÑÐ°
titleType: Subtitle
title: Detecting "smart building" attacks using machine learning techniques
Creators: name: ÐÐ²Ð°Ð½Ð¾Ð², ÐÐ¸ÑÐ°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: ÑÐ¼Ð½Ð¾Ðµ Ð·Ð´Ð°Ð½Ð¸Ðµ
BACnet
Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð²ÑÐ¾ÑÐ¶ÐµÐ½Ð¸Ð¹
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ñ ÑÑÐ¸ÑÐµÐ»ÐµÐ¼
smart building
intrusion detection
supervised learning

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÐ±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð°ÑÐ°Ðº Ð½Ð° "ÑÐ¼Ð½ÑÐµ Ð·Ð´Ð°Ð½Ð¸Ñ" Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸ÑÂ».Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐµÑÐµÐ½Ð¸Ðµ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐ¾ÑÐ¶ÐµÐ½Ð¸Ð¹ Ð² ÑÐµÑÐ¸ BACnet Ð² ÑÑÐµÐ´Ðµ âÑÐ¼Ð½Ð¾Ð³Ð¾ Ð·Ð´Ð°Ð½Ð¸Ñâ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ñ ÑÑÐ¸ÑÐµÐ»ÐµÐ¼. ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ¸ÑÑÐµÐ¼Ð°, Ð¾Ð±ÐµÑÐ¿ÐµÑÐ¸Ð²Ð°ÑÑÐ°Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð°Ð½Ð¾Ð¼Ð°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ ÑÑÑÑÐ¾Ð¹ÑÑÐ² Ð² ÑÑÐµÐ´Ðµ âÑÐ¼Ð½Ð¾Ð³Ð¾ Ð·Ð´Ð°Ð½Ð¸Ñâ. ÐÐ°Ð´Ð°ÑÐ¸, ÑÐµÑÐ°ÐµÐ¼ÑÐµ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ:ÐÐ½Ð°Ð»Ð¸Ð· Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½ÑÑ Ð°ÑÐ°Ðº Ð² ÑÐµÑÐ¸ BACnet Ð² ÑÑÐµÐ´Ðµ âÑÐ¼Ð½Ð¾Ð³Ð¾ Ð·Ð´Ð°Ð½Ð¸Ñâ.ÐÐ½Ð°Ð»Ð¸Ð· Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¿ÑÐ¸Ð¼ÐµÐ½Ð¸Ð¼ÑÑ Ð² ÑÐ¸ÑÑÐµÐ¼Ð°Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐ¾ÑÐ¶ÐµÐ½Ð¸Ð¹.Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° ÑÐ¼ÑÐ»ÑÑÐ¾ÑÐ° âÑÐ¼Ð½Ð¾Ð³Ð¾ Ð·Ð´Ð°Ð½Ð¸Ñâ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐµÐ³Ð¾ Ð¿ÑÐ¾ÑÐ¾ÐºÐ¾Ð» BACnet Ð¸ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑÐµÐ³Ð¾ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÑ Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ñ ÐºÐ°Ðº Ð¾Ð±ÑÑÐ½Ð¾Ð³Ð¾, ÑÐ°Ðº Ð¸ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ°.ÐÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ðµ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð² ÑÐµÑÐµÐ½Ð¸Ð¸ Ð·Ð°Ð´Ð°ÑÐ¸ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð°ÑÐ°Ðº Ð² ÑÐµÑÐ¸ BACnet.Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð¸ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ñ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐ° ÑÐµÑÐ¸ BACnet ÑÐ¼Ð½Ð¾Ð³Ð¾ Ð·Ð´Ð°Ð½Ð¸Ñ Ð¸ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½ÑÐµ Ð°ÑÐ°ÐºÐ¸ Ð½Ð° ÑÑÑ ÑÐµÑÑ. ÐÑÐ»Ð¸ Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ðµ Ð¼ÐµÑÐ¾Ð´Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑÐ¸Ðµ Ð²ÑÑÐ²Ð»ÑÑÑ Ð°ÑÐ°ÐºÐ¸ Ð² ÑÐµÑÐ¸ BACnet.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 ÑÐ¼ÑÐ»ÑÑÐ¾Ñ, Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑÐ¸Ð¹ Ð³ÐµÐ½ÐµÑÐ¸ÑÐ¾Ð²Ð°ÑÑ ÐºÐ°Ðº Ð½Ð¾ÑÐ¼Ð°Ð»ÑÐ½ÑÐ¹ ÑÑÐ°ÑÐ¸Ðº ÑÐµÑÐ¸ BACnet, ÑÐ°Ðº Ð¸ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÐ¹. ÐÑÐ» Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð² Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ð¸ Ð°ÑÐ°Ðº Ð½Ð° ÑÐµÑÑ BACnet.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¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐ¸ÑÑÐµÐ¼Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð²ÑÐ¾ÑÐ¶ÐµÐ½Ð¸Ð¹ Ð² ÑÐµÑÐ¸ BACnet ÑÐ¼Ð½Ð¾Ð³Ð¾ Ð·Ð´Ð°Ð½Ð¸Ñ.
description: The topic of the graduate qualification work is Â«Detecting attacks on smart buildings using machine learning methodsÂ».The purpose of the study is to solve the problem of intrusion detection in the BACnet network in the âsmart buildingâ environment using supervised machine learning methods. The subject of the work is a system that detects anomalous behavior of devices in a smart building environment. The research set the following goals:Analysis of possible attacks in the BACnet network in the âsmart buildingâ environment.Analysis of machine learning methods applicable in intrusion detection systems.Development of a âsmart buildingâ emulator using the BACnet protocol and allowing the generation of both normal and malicious network traffic.Carrying out of a comparative analysis of the effectiveness of machine learning methods in solving the problem of detecting attacks in the BACnet network.In the course of the work, the architecture of the BACnet network of a smart building and possible attacks on this network were investigated. The existing machine learning methods were analyzed to detect attacks in the BACnet network.As a result of the work, an emulator was developed that allows generating both normal BACnet network traffic and malicious traffic. A comparative analysis of the effectiveness of machine learning methods in detecting attacks on the BACnet network was carried out.The results could be used as a base for designing an intrusion detection system in the BACnet network of a smart building.