Multimodel-Based Incident Prediction and Risk Assessment in Dynamic Cybersecurity Protection for Industrial Control Systems

Zhang, Qi; Zhou, Chunjie; Xiong, Naixue; Qin, Yuanqing; Li, Xuan; Huang, Shuang

doi:10.1109/tsmc.2015.2503399

Cited by 114 publications

(57 citation statements)

References 39 publications

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“…Noting thatG α=0 (x) = x, we have p c,t = t = 1/[qG 1 (1)] and p c (TA) = p c (RA) by (16) and (2). Now, we turn to the relative size of the giant component.…”

Section: Discussionmentioning

confidence: 99%

“…Important applications in the security community, for example, include identification of missing person in a family tree or people wanted by the police as suspects in a crime. A node-based incident prediction approach is proposed in [16], which has applications in industrial control systems. This problem is significantly more difficult than the link prediction problem as neither the nodes nor their edges are known with certainty [17].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Subgraph Robustness of Complex Networks Under Attacks

Shang

2019

IEEE Trans. Syst. Man Cybern, Syst.

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Network measures derived from empirical observations are often poor estimators of the true structure of system as it is impossible to observe all components and all interactions in many real world complex systems. Here, we study attack robustness of complex networks with data missing caused by (i) a uniform random sampling and (ii) a non-uniform random sampling. By introducing the subgraph robustness problem, we develop analytically a framework to investigate robustness properties of the two types of subgraphs under random attacks, localized attacks, and targeted attacks. Interestingly, we find that the benchmark models such as Erdős-Rényi graphs, random regular networks, and scale-free networks possess distinct characteristic subgraph robustness features. We show that the network robustness depends on several factors including network topology, attack mode, sampling method and the amount of data missing, generalizing some well-known robustness principles of complex networks. Our results offer insight into the structural effect of missing data in networks and highlight the significance of understanding different sampling processes and their consequences on attack robustness, which may be instrumental in designing robust systems.

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“…Noting thatG α=0 (x) = x, we have p c,t = t = 1/[qG 1 (1)] and p c (TA) = p c (RA) by (16) and (2). Now, we turn to the relative size of the giant component.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Subgraph Robustness of Complex Networks Under Attacks

Shang

2019

IEEE Trans. Syst. Man Cybern, Syst.

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“…Existing cyber security risk frameworks for ICS fall into three main categories: i) international/national standards and guidelines on ICS cyber security [1]- [3]; ii) quantitative risk assessment [4], [5]; and iii) attack tree approaches [6]- [8]. Standards provide a high level guidance for improving and managing cyber security risks in ICS contexts.…”

Section: Related Workmentioning

confidence: 99%

Understanding Security Requirements for Industrial Control System Supply Chains

Hou

Such

Rashid

2019

2019 IEEE/ACM 5th International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS)

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We address the need for security requirements to take into account risks arising from complex supply chains underpinning cyber-physical infrastructures such as industrial control systems (ICS). We present SEISMiC (SEcurity Industrial control SysteM supply Chains), a framework that takes into account the whole spectrum of security risks-from technical aspects through to human and organizational issues-across an ICS supply chain. We demonstrate the effectiveness of SEISMiC through a supply chain risk assessment of Natanz, Iran's nuclear facility that was the subject of the Stuxnet attack. Index Terms-security requirements, cyber-physical systems, risk decision-making, supply chains.

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“…Protecting ICS from cyber-attacks is critical to a country's economic development and social stability. ICS's network security problem must be taken seriously [5]. Information security risk assessment of industrial control systems can effectively help users to identify potential system risks and take appropriate defensive measures, which has become the focus of current industrial research.…”

Section: Introductionmentioning

confidence: 99%

Information Security Risk Assessment Method for Ship Control System Based on Fuzzy Sets and Attack Trees

Shang

Gong

Chen

et al. 2019

Security and Communication Networks

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Information security risk assessment for industrial control system is usually influenced by uncertain factors. For effectively dealing with problem that the uncertainty and quantification difficulties are caused by subjective and objective factors in the assessment process, an information security risk assessment method based on attack tree model with fuzzy set theory and probability risk assessment technology is proposed, which is applied in a risk scenario of ship control system. Firstly, potential risks of the control system are analyzed and the attack tree model is established. Then triangular fuzzy numbers and expert knowledge are used to determine the factors that influence the probability of a leaf node and the leaf nodes are quantified to obtain the interval probability. Finally, the fuzzy arithmetic is used to determine the interval probability of the root node and the attack path. After defuzzification, the potential risks of the system and the probability of occurrence of each attack path are obtained. Compared with other methods, the proposed method can greatly reduce the impact of subjectivity on the risk assessment of industrial control systems and get more stable, reliable, and scientific evaluation results.

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Multimodel-Based Incident Prediction and Risk Assessment in Dynamic Cybersecurity Protection for Industrial Control Systems

Cited by 114 publications

References 39 publications

Subgraph Robustness of Complex Networks Under Attacks

Subgraph Robustness of Complex Networks Under Attacks

Understanding Security Requirements for Industrial Control System Supply Chains

Information Security Risk Assessment Method for Ship Control System Based on Fuzzy Sets and Attack Trees

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