BACGraph: Automatic Extraction of Object Relationships in the BACnet Protocol

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Downloads (Pure)

Abstract

This work presents BACGRAPH, a tool that extracts relationships among configuration parameters of Building Automation and Control Systems (BACSs) implemented using the BACnet protocol (ISO 16484-5). BACnet models these configuration parameters as object data structures comprised of multiple properties, some of which contain references to other objects. Given the regular exchange of objects among devices, we leverage these explicit references to build a graph of BACnet objects exclusively from network traffic. We tested BACGRAPH using traffic collected from a real building located at the University of Twente. After analyzing 66.8 hours of traffic, the resulting graph is comprised of 13,733 nodes and 3,169 edges. Such a graph improves the system visibility that BACS administrators have over their infrastructure, which is crucial for troubleshooting and security.
Original languageEnglish
Title of host publication2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages45-48
Number of pages4
ISBN (Electronic)978-1-6654-3566-6
ISBN (Print)978-1-6654-0252-1
DOIs
Publication statusPublished - Jun 2021
Event51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume, DSN-S 2021 - Taipei, Taiwan
Duration: 21 Jun 202124 Jun 2021
Conference number: 51

Conference

Conference51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume, DSN-S 2021
CountryTaiwan
CityTaipei
Period21/06/2124/06/21

Fingerprint

Dive into the research topics of 'BACGraph: Automatic Extraction of Object Relationships in the BACnet Protocol'. Together they form a unique fingerprint.

Cite this