A History of Cyber Incidents and Threats Involving Industrial Control Systems

Hemsley, Kevin E.; Fisher, Ronald E.

doi:10.1007/978-3-030-04537-1_12

Cited by 28 publications

(55 citation statements)

References 2 publications

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“…According to the literature review on the major ICS attack events [4], most of the attacks have involved abnormal network behaviors. On the other hand, the literature review also has demonstrated MLtechniques yield effective classification and LSTM is suitable for time-series data.…”

Section: Proposed Methodologymentioning

confidence: 99%

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A Study of Identifying Attacks on Industry Internet of Things Using Machine Learning

Chen¹,

Cai²,

Lai³

2021

Computer Science &Amp; Information Technology (CS &Amp; IT)

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The “Industry 4.0” revolution and Industry Internet of Things (IIoT) has dramatically transformed how manufacturing and industrial companies operate. Industrial control systems (ICS) process critical function, and the past ICS attacks have caused major damage and disasters in the communities. IIoT devices in an ICS environment communicate in heterogeneous protocols and the attack vectors might exhibit different misbehavior patterns. This study proposes a classification model to detect anomalies in ICS environments. The evaluation has been conducted by using ICS datasets from multiple sources and the results show that the proposed LSTM detection model performs effectively.

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Section: Proposed Methodologymentioning

confidence: 99%

“…The attacks are expected to increase in number and sophistication. Therefore, critical infrastructure owners and operators must develop the ability to detect and recover from cyberattacks [4]. Therefore, protecting ICS and IIoT networks is critical for enterprises and industries.…”

Section: Introductionmentioning

confidence: 99%

A Study of Identifying Attacks on Industry Internet of Things Using Machine Learning

Chen¹,

Cai²,

Lai³

2021

Computer Science &Amp; Information Technology (CS &Amp; IT)

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“…It has been reported that both the C37.118 and IEC 61850 communication architectures might be vulnerable to cyber attacks [5]. Recent real-world cyber attacks on energy industrial control systems, such as the 2015 Black Energy attacks [6] and the 2017 Dragonfly 2.0 campaign [7], further highlight the importance of securing electrical power control systems.…”

Section: Introductionmentioning

confidence: 99%

Game theoretic vulnerability management for secondary frequency control of islanded microgrids against false data injection attacks

Liu

Chen

2021

IET Cyber-Phy Sys Theory & Ap

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While most existing works ignore securing the communication of control signals in microgrids' centralized secondary frequency control, here, a stochastic game between the microgrid control centre (MGCC) and the attacker for enhancing the vulnerability of the MGCC to false data injection (FDI) attack (wireless spoof attack) is proposed. The vulnerability to wireless spoof attack is assessed based on the controllability Gramian when the FDI attack is modelled as the malicious control input that aims to drive the microgrid state to undesired values. In the formulated zero-sum two-player Markov game, the state is uniquely associated with the vulnerability index defined by the trace of the controllability Gramian with respect to the attack input. Moreover, the utility function of the stochastic game includes not only the costs related to conducting spoof attack and encryption actions but also the possible remedy costs associated with the resulted vulnerability levels. In turn, the potential impacts of the cyber-layer action choices on the performance of the physical power system are considered when designing the optimal attack and defence strategies. A distribution feeder system with four distributed generators (DGs) is used for simulation studies. The vulnerability assessment results show that the vulnerability level increases when the attacker compromises more on the communication links between the MGCC and DGs. In the simulated game, mixed stationary attack and defence strategies are predominate when considering the uncertainty of the other player.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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“…As more critical infrastructures and industrial processes are connected via communication networks the threat of cyber-attacks on these systems increases rapidly (Hemsley and Fisher, 2018). The attacks can range from sophisticated attacks, such as the Stuxnet attack on an Iranian uranium enrichment facility (Kushner, 2013), to attacks where the attacker takes over the whole control system as in the attack on the Ukranian power grid (Lee et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Experimental evaluation of sensor attacks and defense mechanisms in feedback systems

Umsonst,

Sandberg

2021

Preprint

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In this work, we evaluate theoretical results on the feasibility of, the worst-case impact of, and defense mechanisms against a stealthy sensor attack in an experimental setup. We demonstrate that for a controller with stable dynamics the stealthy sensor attack is possible to conduct and the theoretical worst-case impact is close to the achieved practical one. However, although the attack should theoretically be possible when the controller has integral action, we show that the integral action slows the attacker down and the attacker is not able to remain stealthy if it has not perfect knowledge of the controller state. In addition to that, we investigate the effect of different anomaly detectors on the attack impact and conclude that the impact under detectors with internal dynamics is smaller. Finally, we use noise injection into the controller dynamics to unveil the otherwise stealthy attacks.

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A History of Cyber Incidents and Threats Involving Industrial Control Systems

Cited by 28 publications

References 2 publications

A Study of Identifying Attacks on Industry Internet of Things Using Machine Learning

A Study of Identifying Attacks on Industry Internet of Things Using Machine Learning

Game theoretic vulnerability management for secondary frequency control of islanded microgrids against false data injection attacks

Experimental evaluation of sensor attacks and defense mechanisms in feedback systems

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