Publication Details

Efficient Modelling of ICS Communication For Anomaly Detection Using Probabilistic Automata

MATOUŠEK Petr, HAVLENA Vojtěch and HOLÍK Lukáš. Efficient Modelling of ICS Communication For Anomaly Detection Using Probabilistic Automata. In: Proceedings of IFIP/IEEE International Symposium on Integrated Network Management. Bordeaux: International Federation for Information Processing, 2021, pp. 81-89. ISBN 978-3-903176-32-4. Available from: http://dl.ifip.org/db/conf/im/im2021/210993.pdf
Czech title
Efektivní modelování komunikace ICS pomocí pravděpodobnostních automatů pro detekci anomálií
Type
conference paper
Language
english
Authors
URL
Keywords

ICS, probabilistic automata, network monitoring, anomaly detection, IPFIX, IEC 104

Abstract

Industrial Control System (ICS) communication transmits monitoring and control data between industrial processes and the control station. ICS systems cover various domains of critical infrastructure such as the power plants, water and gas distribution, or aerospace traffic control. Security of ICS systems is usually implemented on the perimeter of the network using ICS enabled firewalls or Intrusion Detection Systems (IDSs). These techniques are helpful against external attacks, however, they are not able to effectively detect internal threats originating from a compromised device with malicious software. In order to mitigate or eliminate internal threats against the ICS system, we need to monitor ICS traffic and detect suspicious data transmissions that differ from common operational communication. In our research, we obtain ICS monitoring data using standardized IPFIX flows extended with meta data extracted from ICS protocol headers. Unlike other anomaly detection approaches, we focus on modelling the semantics of ICS communication obtained from the IPFIX flows that describes typical conversational patterns. This paper presents a technique for modelling ICS conversations using frequency prefix trees and Deterministic Probabilistic Automata (DPA). As demonstrated on the attack scenarios, these models are efficient to detect common cyber attacks like the command injection, packet manipulation, network scanning, or lost connection. An important advantage of our approach is that the proposed technique can be easily integrated into common security information and event management (SIEM) systems with Netflow/IPFIX support. Our experiments are performed on IEC 60870-5-104 (aka IEC 104) control communication that is widely used for the substation control in smart grids.

Published
2021
Pages
81-89
Proceedings
Proceedings of IFIP/IEEE International Symposium on Integrated Network Management
Conference
IFIP/IEEE International Symposium on Integrated Network Management, Bordeaux, FR
ISBN
978-3-903176-32-4
Publisher
International Federation for Information Processing
Place
Bordeaux, FR
UT WoS
000696801700010
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB12385,
   author = "Petr Matou\v{s}ek and Vojt\v{e}ch Havlena and Luk\'{a}\v{s} Hol\'{i}k",
   title = "Efficient Modelling of ICS Communication For Anomaly Detection Using Probabilistic Automata",
   pages = "81--89",
   booktitle = "Proceedings of IFIP/IEEE International Symposium on Integrated Network Management",
   year = 2021,
   location = "Bordeaux, FR",
   publisher = "International Federation for Information Processing",
   ISBN = "978-3-903176-32-4",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12385"
}
Files
Back to top