Security Analysis of CPS Systems Under Different Swapping Strategies in IoT Environments

Peng, Hao; Liu, Can; Zhao, Dandan; Ye, Hongxia; Fang, Zian; Wang, Wei

doi:10.1109/access.2020.2983335

Cited by 23 publications

(12 citation statements)

References 50 publications

(65 reference statements)

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“…Degree centrality is widely utilized to calculate the importance of nodes [ 12 , 28 , 35 ]. It is well-known that the intra-link number of one node is the node’s degree in an undirected network [ 9 , 34 ].…”

Section: Methodsmentioning

confidence: 99%

“…One node’s betweenness centrality is:

where

is the shortest paths number from node i to node j .

is the shortest paths number from node i to node j which are through the node v [ 28 , 34 , 35 ]. If one node has a large number of shortest paths to other nodes, this node must be a critical node in the network.…”

Section: Methodsmentioning

confidence: 99%

“…Because the eigenvector centrality will be changed due to nodes’ neighborhoods, the initial value of node’s eigenvector centrality

. The value of

changes into

[ 34 , 35 ]:

where

is the largest eigenvector value in the matrix A . If a node is connected to multiple important nodes, the importance of the node will increase.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

A Security Scheme Based on Intranal-Adding Links for Integrated Industrial Cyber-Physical Systems

Zhao

Liu

Peng

et al. 2021

Sensors

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With the advent of the Internet of Everything era, the Industrial Internet is increasingly showing mutual integration and development. Its core framework, the industrial CPS (Cyber-Physical Systems), has received more and more attention and in-depth research in recent years. These complex industrial CPS systems are usually composed of multiple interdependent sub-networks (such as physical networks and control networks, etc.). Minor faults or failure behaviors between sub-networks may cause serious cascading failure effects of the entire system. In this paper, we will propose a security scheme based on intranal-adding links in the face of the integrated and converged industrial CPS system environment. Firstly, by calculating the size of the largest connected component in the entire system, we can compare and analyze industrial CPS systems’ security performance under random attacks. Secondly, we compare and analyze the risk of cascading failure between integrated industrial CPS systems under different intranal-adding link strategies. Finally, the simulation results verify the system security strategy’s effectiveness under different strategies and show a relatively better exchange strategy to enhance the system’s security. In addition, this paper’s research work can help us design how to further optimize the interdependent industrial CPS system’s topology to cope with the integrated and converged industrial CPS system environment.

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Section: Methodsmentioning

confidence: 99%

“…One node’s betweenness centrality is:

where

is the shortest paths number from node i to node j .

Section: Methodsmentioning

confidence: 99%

“…Because the eigenvector centrality will be changed due to nodes’ neighborhoods, the initial value of node’s eigenvector centrality

. The value of

changes into

[ 34 , 35 ]:

where

is the largest eigenvector value in the matrix A . If a node is connected to multiple important nodes, the importance of the node will increase.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Security Scheme Based on Intranal-Adding Links for Integrated Industrial Cyber-Physical Systems

Zhao

Liu

Peng

et al. 2021

Sensors

Self Cite

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show abstract

“…Therefore, this method should guarantee that typical data are not affected; this ensures that abnormal data cannot be hidden in the network’s standard information, thereby making the whole process self-defense. It is worth noting that different methods, including increased traffic and information manipulation, can be used to manipulate the network [ 21 ].…”

Section: Related Workmentioning

confidence: 99%

Sequential Model Based Intrusion Detection System for IoT Servers Using Deep Learning Methods

Zhong

Zhou

Chen

2021

Sensors

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IoT plays an important role in daily life; commands and data transfer rapidly between the servers and objects to provide services. However, cyber threats have become a critical factor, especially for IoT servers. There should be a vigorous way to protect the network infrastructures from various attacks. IDS (Intrusion Detection System) is the invisible guardian for IoT servers. Many machine learning methods have been applied in IDS. However, there is a need to improve the IDS system for both accuracy and performance. Deep learning is a promising technique that has been used in many areas, including pattern recognition, natural language processing, etc. The deep learning reveals more potential than traditional machine learning methods. In this paper, sequential model is the key point, and new methods are proposed by the features of the model. The model can collect features from the network layer via tcpdump packets and application layer via system routines. Text-CNN and GRU methods are chosen because the can treat sequential data as a language model. The advantage compared with the traditional methods is that they can extract more features from the data and the experiments show that the deep learning methods have higher F1-score. We conclude that the sequential model-based intrusion detection system using deep learning method can contribute to the security of the IoT servers.

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“…Security is deployed for both physical devices and network resources that are connected through application interfaces. 1 The protection is evaluated to improve the safeguarding of the information from the attacks and provides authenticated verification. 2 The verification is obtained by determining the cybersecurity mechanism that acquires the data from the user and derives the resultant information.…”

Section: Introductionmentioning

confidence: 99%

Replication‐aware secure resource administration scheme for Internet of Things‐smart city applications

Solami

2021

Trans Emerging Tel Tech

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The distributed and heterogeneous nature of the Internet of Things (IoT) paradigm provides backhauled support for different smart-city applications. As it provides ubiquitous access to resources and replicated services, the threat for security remains firm for different applications. The concept of cybersecurity in the IoT-smart-city combination grants promising outcomes in securing the physical and service-centric resources from external threats. This article proposes to improve the protection of the IoT services in smart-city applications using replication-aware secure resource administration scheme framework. In a smart city application, which involves a cloud, based network, IoT platform, and distributed sensor networks guarantees differentiated protection mechanisms for replicated and non-replicated infrastructure. Instantly revocable security activities are used to prevent unintended attacks to the original resource supplier from monitoring non-replicated services. For this purpose, Naïve Bayes' diffusion approach is used to continuously evaluate the likelihood of disclosure of the repeated and unreplicated properties. The hazard and level of exposure for which prompted protection is assessed using the recommendations of the delivery system. The promptness of the security outcome is based on re-formulating permission delegations, security checks, and so on. This helps to leverage the security level of the available resources irrespective of the impact of the external threats. Besides, the proposed scheme improves the lifetime of the services with controlled overhead and service failures.

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Security Analysis of CPS Systems Under Different Swapping Strategies in IoT Environments

Cited by 23 publications

References 50 publications

A Security Scheme Based on Intranal-Adding Links for Integrated Industrial Cyber-Physical Systems

A Security Scheme Based on Intranal-Adding Links for Integrated Industrial Cyber-Physical Systems

Sequential Model Based Intrusion Detection System for IoT Servers Using Deep Learning Methods

Replication‐aware secure resource administration scheme for Internet of Things‐smart city applications

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