Security in building automation systems - a first analysis

Mundt, Thomas; Wickboldt, Peter

doi:10.1109/cybersecpods.2016.7502336

Cited by 28 publications

(23 citation statements)

References 12 publications

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“…After that, s/he obtained access to the Installation Bus and was able to collect data transmitted over the network (e.g., data exchanged between the Workstation and the HVAC). This was possible because messages exchanged through the installation bus are not encrypted [9]. The offender then sent a targeted Malware (e.g., exploiting the vulnerabilities present in Trane HVACs [10]) to disable the HVAC, subsequently causing the Servers to heat up.…”

Section: Motivating Examplementioning

confidence: 99%

Incidents are Meant for Learning, Not Repeating: Sharing Knowledge About Security Incidents in Cyber-Physical Systems

Alrimawi

Pasquale

Mehta

et al. 2022

IIEEE Trans. Software Eng.

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Cyber-physical systems (CPSs) are part of most critical infrastructures such as industrial automation and transportation systems. Thus, security incidents targeting CPSs can have disruptive consequences to assets and people. As prior incidents tend to re-occur, sharing knowledge about these incidents can help organizations be more prepared to prevent, mitigate or investigate future incidents. This paper proposes a novel approach to enable representation and sharing of knowledge about CPS incidents across different organizations. To support sharing, we represent incident knowledge (incident patterns) capturing incident characteristics that can manifest again, such as incident activities or vulnerabilities exploited by offenders. Incident patterns are a more abstract representation of specific incident instances and, thus, are general enough to be applicable to various systems -different than the one in which the incident occurred. They can also avoid disclosing potentially sensitive information about an organization's assets and resources. We provide an automated technique to extract an incident pattern from a specific incident instance. To understand how an incident pattern can manifest again in other cyberphysical systems, we also provide an automated technique to instantiate incident patterns to specific systems. We demonstrate the feasibility of our approach in the application domain of smart buildings. We evaluate correctness, scalability, and performance using two substantive scenarios inspired by real-world systems and incidents.

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Section: Motivating Examplementioning

confidence: 99%

Incidents are Meant for Learning, Not Repeating: Sharing Knowledge About Security Incidents in Cyber-Physical Systems

Alrimawi

Pasquale

Mehta

et al. 2022

IIEEE Trans. Software Eng.

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“…There have been a number of recent works on BAS security. In [6], Mundt et al concluded several weaknesses in modern BASs ranging from field layer to automation and management layer, based on practical attacks against two office buildings where KNX and BACnet were deployed. Brauchli et al in [7] conducted their security assessment on a real home automation system, digitalSTORM, and derived attack vectors of BASs involving servers, devices, the communication bus and remote access.…”

Section: Related Workmentioning

confidence: 99%

A Taxonomy for the Security Assessment of IP-Based Building Automation Systems: The Case of Thread

Liu

Pang

Dán

et al. 2018

IEEE Trans. Ind. Inf.

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Motivated by the proliferation of wireless building automation systems (BAS) and increasing security-awareness among BAS operators, in this paper we propose a taxonomy for the security assessment of BASs. We apply the proposed taxonomy to Thread, an emerging native IP-based protocol for BAS. Our analysis reveals a number of potential weaknesses in the design of Thread. We propose potential solutions for mitigating several identified weaknesses and discuss their efficacy. We also provide suggestions for improvements in future versions of the standard. Overall, our analysis shows that Thread has a well-designed security control for the targeted use case, making it a promising candidate for communication in next generation BASs.

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“…Consequently, data related to these actions might not be collected and stored proactively, hence, any future investigations of similar incidents might be more difficult because some relevant evidence is missing. Moreover, identifying vulnerabilities in a system can be difficult, since a system as a smart building can contain several hundreds of components with various vulnerabilities that can be exploited [13]. Some vulnerabilities can be thus overlooked due to human errors.…”

Section: Motivating Examplementioning

confidence: 99%

I've seen this before

Alrimawi

Pasquale

Mehta

et al. 2018

Proceedings of the 1st International Workshop on Security Awareness From Design to Deployment

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An increasing number of security incidents in cyber-physical systems (CPSs) arise from the exploitation of cyber and physical components of such systems. Knowledge about how such incidents arose is rarely captured and used systematically to enhance security and support future incident investigations. In this paper, we propose an approach to represent and share incidents knowledge. Our approach captures incident patterns -common aspects of incidents occurring in different CPSs. Our approach then allows incident patterns to be instantiated for different systems to assess if and how such patterns can manifest again. To support our approach, we provide two meta-models that represent, respectively, incident patterns and the cyber-physical systems themselves. The incident meta-model captures the characteristics of incidents, such as assets and activities. The system meta-model captures cyber and physical components and their interactions, which may be exploited during an incident. We demonstrate the feasibility of our approach in the application domain of smart buildings, by tailoring the system meta-model to represent components and interactions in this domain. CCS CONCEPTS• Software and its engineering → Model-driven software engineering KEYWORDS

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Security in building automation systems - a first analysis

Cited by 28 publications

References 12 publications

Incidents are Meant for Learning, Not Repeating: Sharing Knowledge About Security Incidents in Cyber-Physical Systems

Incidents are Meant for Learning, Not Repeating: Sharing Knowledge About Security Incidents in Cyber-Physical Systems

A Taxonomy for the Security Assessment of IP-Based Building Automation Systems: The Case of Thread

I've seen this before

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