Proceedings of the 2017 Workshop on Cyber-Physical Systems Security and PrivaCy 2017
DOI: 10.1145/3140241.3140244
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Automatic Deployment of Specification-based Intrusion Detection in the BACnet Protocol

Abstract: Specification-based intrusion detection (SB-ID) is a suitable approach to monitor Building Automation Systems (BASs) because the correct and non-compromised functioning of the system is well understood. Its main drawback is that the creation of specifications often require human intervention. We present the first fully automated approach to deploy SB-ID at network level. We do so in the domain of BASs, specifically, the BACnet protocol (ISO 16484-5). In this protocol, properly certified devices are demanded to… Show more

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Cited by 19 publications
(26 citation statements)
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“…Larson et al in [29] employ the CAN protocol version 2 and the CANOpen application layer draft standard 3.01 as specification source to extract the expected behaviour of electronic control unit of an in-vehicle network. Also, Esquivel-Vargas et al in [30] exploit the Building Automation and Control Networks (BACnet) protocol as specification source to depict the normal behaviour of each device in the BACnet network.…”
Section: A Specification Sourcementioning
confidence: 99%
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“…Larson et al in [29] employ the CAN protocol version 2 and the CANOpen application layer draft standard 3.01 as specification source to extract the expected behaviour of electronic control unit of an in-vehicle network. Also, Esquivel-Vargas et al in [30] exploit the Building Automation and Control Networks (BACnet) protocol as specification source to depict the normal behaviour of each device in the BACnet network.…”
Section: A Specification Sourcementioning
confidence: 99%
“…2) Automatic: Efforts have been made in recent years to extract the correct system behaviour from the specification source automatically [30], [34], [28]. Esquivel-Vargas et al in [30] made the first attempt to extract specification automatically.…”
Section: B Specification Extractionmentioning
confidence: 99%
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