A Survey of IoT-Enabled Cyberattacks: Assessing Attack Paths to Critical Infrastructures and Services

Stellios, Ioannis; Kotzanikolaou, Panayiotis; Psarakis, Mihalis; Alcaraz, Cristina; López, Javier

doi:10.1109/comst.2018.2855563

Cited by 312 publications

(202 citation statements)

References 128 publications

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“…In 2018, Stellios et al [30] discussed the Internet of Things (IoT) enabled cyberattacks in several critical infrastructures (CIs), e.g., industry, smart grid, transportation, and healthcare. The authors modeled a threat vector that can be used against IoT devices.…”

Section: A Existing Workmentioning

confidence: 99%

“…Some of the work presented in [21], [25], [26], and [30] categorized many of security issues, for instance smart grid to home and vice versa, security analytics, physical and cybersecurity, and IoT enabled attacks in CIs, respectively, in SG. None of the existing survey covers recent real-time attack incidents on the energy networks, except the work presented in [30]. Other works [23], [27] and [28] focus on privacy in SG metering networks and present high level solutions with limited analysis.…”

Section: B Comparison With Our Surveymentioning

confidence: 99%

“…6 shows the high-level adversary model, including adversaries, vulnerabilities and targets. The threat model followed in this paper is conceptually adopted from [30].…”

Section: A Threat Modeling In Sg Metering Networkmentioning

confidence: 99%

“…In our high-level threat model (refer to Fig. 6), we regard the interconnection between the systems and targets, as direct connectivity, and indirect connectivity [30]. Based on the connections, an attacker may exercise an attack to a target, as follows.…”

Section: A3 the Targets In Sg Metering Networkmentioning

confidence: 99%

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Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

Kumar

Lin

Bai

et al. 2019

IEEE Commun. Surv. Tutorials

250

115

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Smart grid (SG) networks are newly upgraded networks of connected objects that greatly improve reliability, efficiency and sustainability of the traditional energy infrastructure. In this respect, the smart metering infrastructure (SMI) plays an important role in controlling, monitoring and managing multiple domains in the SG. Despite the salient features of SMI, security and privacy issues have been under debate because of the large number of heterogeneous devices that are anticipated to be coordinated through public communication networks. This survey paper shows a brief overview of real cyber attack incidents in traditional energy networks and those targeting the smart metering network. Specifically, we present a threat taxonomy considering: (i) threats in system-level security, (ii) threats and/or theft of services, and (iii) threats to privacy. Based on the presented threats, we derive a set of security and privacy requirements for SG metering networks. Furthermore, we discuss various schemes that have been proposed to address these threats, considering the pros and cons of each. Finally, we investigate the open research issues to shed new light on future research directions in smart grid metering networks.

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Section: A Existing Workmentioning

confidence: 99%

Section: B Comparison With Our Surveymentioning

confidence: 99%

“…6 shows the high-level adversary model, including adversaries, vulnerabilities and targets. The threat model followed in this paper is conceptually adopted from [30].…”

Section: A Threat Modeling In Sg Metering Networkmentioning

confidence: 99%

Section: A3 the Targets In Sg Metering Networkmentioning

confidence: 99%

See 2 more Smart Citations

Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

Kumar

Lin

Bai

et al. 2019

IEEE Commun. Surv. Tutorials

250

115

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“…We consider four data security dimensions: integrity, authenticity, confidentiality and privacy. For more details on the state‐of‐the‐art, we refer the reader to a number of excellent surveys presenting the state‐of‐the‐art in security in IoT …”

Section: State Of the Art/related Workmentioning

confidence: 99%

A systematic approach toward security in Fog computing: Assets, vulnerabilities, possible countermeasures

et al. 2020

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Fog computing is an emerging paradigm in the Internet of Things (IoT) space, consisting of a middle computation layer, sitting between IoT devices and Cloud servers. Fog computing provides additional computing, storage, and networking resources in close proximity to where data is being generated and/or consumed. As the Fog layer has direct access to data streams generated by IoT devices and responses/commands sent from the Cloud, it is in a critical position in terms of security of the entire IoT system. Currently, there is no specific tool or methodology for analysing the security of Fog computing systems in a comprehensive way.Generic security evaluation procedures applicable to most information technology products are time consuming, costly, and badly suited to the Fog context. In this article, we introduce a methodology for evaluating the security of Fog computing systems in a systematic way. We also apply our methodology to a generic Fog computing system, showcasing how it can be purposefully used by security analysts and system designers. K E Y W O R D Sattack, common criteria, fog computing, methodology, security INTRODUCTIONFog computing is an emerging technology which enriches Cloud computing with additional compute, storage and networking resources in close proximity with the end-user devices which generate and/or consume data streams. 1 With the development of Internet of Things (IoT) systems and applications, increasing volumes of data are being produced by IoT devices at the edges of the network. In this situation, it is often not feasible to send all IoT data to a remote Cloud data center and expect acceptable Quality of Service, especially for applications with low-latency requirements such as augmented reality, industrial control systems, and video streaming. Moreover, many applications such as quantified self which use wearable sensors to monitor individuals life often deal with sensitive personal data. In solely Cloud-based approaches for these applications, all these sensitive data would be sent to the Cloud for processing, leaving the user with little control over the usage of their data.An IoT system architecture with support of Fog computing comprises at least the following three layers: 2 (a) An IoT device layer (comprising the actual sensors and actuators); (b) A Fog computing layer located very close to the IoT devices; and (c) A Cloud computing layer.Fog computing therefore acts as a middle layer, sitting between the Cloud and the IoT devices. Depending on the application, some parts of the computation may be delegated to the Fog layer, which prevents one from having to send Softw: Pract Exper. 2020;50:973-997. wileyonlinelibrary.com/journal/spe © 2020 John Wiley & Sons, Ltd. 973 974 FARHADI et al.raw data to the Cloud. As Fog computing servers process local data locally, we also expect a lower usage of long-distance network bandwidth as well as reduced response times. Also, the user data are now processed by computing elements which are geographically close to where data is generated, l...

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Network Attacks and Protection

2022

Cyber Infrastructure for the Smart Electric Grid

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A Survey of IoT-Enabled Cyberattacks: Assessing Attack Paths to Critical Infrastructures and Services

Cited by 312 publications

References 128 publications

Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

A systematic approach toward security in Fog computing: Assets, vulnerabilities, possible countermeasures

Network Attacks and Protection

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