Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital Forensic
The Siemens S7 protocol is commonly used in SCADA systems for communications between a Human Machine Interface (HMI) and the Programmable Logic Controllers (PLCs). This paper presents a model-based Intrusion Detection Systems (IDS) designed for S7 networks. The approach is based on the key observati...
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2014-09-01
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doaj-a3acaffac2214abfadc01f8c6ea0a7772020-11-25T02:50:05ZengAssociation of Digital Forensics, Security and LawJournal of Digital Forensics, Security and Law1558-72151558-72232014-09-01923750168Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital ForensicAmit Kleinmann0Avishai Wool1Tel-Aviv UniversityTel-Aviv UniversityThe Siemens S7 protocol is commonly used in SCADA systems for communications between a Human Machine Interface (HMI) and the Programmable Logic Controllers (PLCs). This paper presents a model-based Intrusion Detection Systems (IDS) designed for S7 networks. The approach is based on the key observation that S7 traffic to and from a specific PLC is highly periodic; as a result, each HMI-PLC channel can be modeled using its own unique Deterministic Finite Automaton (DFA). The resulting DFA-based IDS is very sensitive and is able to flag anomalies such as a message appearing out of its position in the normal sequence or a message referring to a single unexpected bit. The intrusion detection approach was evaluated on traffic from two production systems. Despite its high sensitivity, the system had a very low false positive rate - over 99.82% of the traffic was identified as normal.http://ojs.jdfsl.org/index.php/jdfsl/article/view/262 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Amit Kleinmann Avishai Wool |
spellingShingle |
Amit Kleinmann Avishai Wool Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital Forensic Journal of Digital Forensics, Security and Law |
author_facet |
Amit Kleinmann Avishai Wool |
author_sort |
Amit Kleinmann |
title |
Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital Forensic |
title_short |
Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital Forensic |
title_full |
Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital Forensic |
title_fullStr |
Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital Forensic |
title_full_unstemmed |
Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital Forensic |
title_sort |
accurate modeling of the siemens s7 scada protocol for intrusion detection and digital forensic |
publisher |
Association of Digital Forensics, Security and Law |
series |
Journal of Digital Forensics, Security and Law |
issn |
1558-7215 1558-7223 |
publishDate |
2014-09-01 |
description |
The Siemens S7 protocol is commonly used in SCADA systems for communications between a Human Machine Interface (HMI) and the Programmable Logic Controllers (PLCs). This paper presents a model-based Intrusion Detection Systems (IDS) designed for S7 networks. The approach is based on the key observation that S7 traffic to and from a specific PLC is highly periodic; as a result, each HMI-PLC channel can be modeled using its own unique Deterministic Finite Automaton (DFA). The resulting DFA-based IDS is very sensitive and is able to flag anomalies such as a message appearing out of its position in the normal sequence or a message referring to a single unexpected bit. The intrusion detection approach was evaluated on traffic from two production systems. Despite its high sensitivity, the system had a very low false positive rate - over 99.82% of the traffic was identified as normal. |
url |
http://ojs.jdfsl.org/index.php/jdfsl/article/view/262 |
work_keys_str_mv |
AT amitkleinmann accuratemodelingofthesiemenss7scadaprotocolforintrusiondetectionanddigitalforensic AT avishaiwool accuratemodelingofthesiemenss7scadaprotocolforintrusiondetectionanddigitalforensic |
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