scholarly journals Research on network security technology of industrial control system

2022 ◽  
Vol 355 ◽  
pp. 03067
Author(s):  
Kai Jin ◽  
Zhanji Niu ◽  
Jieping Liu ◽  
Jinxue Bai ◽  
Lei Zhang
Keyword(s):  
Control System ◽  
Network Security ◽  
Industrial Control System ◽  
Security Technology ◽  
Industrial Control ◽  
Penetration Testing ◽  
Network Intrusion ◽  
Detection Technology ◽  
Testing Technology ◽  
The Relationship

The relationship between industrial control system and Internet is becoming closer and closer, and its network security has attracted much attention. Penetration testing is an active network intrusion detection technology, which plays an indispensable role in protecting the security of the system. This paper mainly introduces the principle of penetration testing, summarizes the current cutting-edge penetration testing technology, and looks forward to its development.

scholarly journals Explaining the Attributes of a Deep Learning Based Intrusion Detection System for Industrial Control Networks

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3817 ◽  
Author(s):  
Zhidong Wang ◽  
Yingxu Lai ◽  
Zenghui Liu ◽  
Jing Liu
Keyword(s):  
Deep Learning ◽  
Control System ◽  
Intrusion Detection ◽  
Security System ◽  
Classification Model ◽  
Industrial Control System ◽  
Industrial Control ◽  
Data Set ◽  
Network Intrusion ◽  
Calculation Process

Intrusion detection is only the initial part of the security system for an industrial control system. Because of the criticality of the industrial control system, professionals still make the most important security decisions. Therefore, a simple intrusion alarm has a very limited role in the security system, and intrusion detection models based on deep learning struggle to provide more information because of the lack of explanation. This limits the application of deep learning methods to industrial control network intrusion detection. We analyzed the deep neural network (DNN) model and the interpretable classification model from the perspective of information, and clarified the correlation between the calculation process of the DNN model and the classification process. By comparing the normal samples with the abnormal samples, the abnormalities that occur during the calculation of the DNN model compared to the normal samples could be found. Based on this, a layer-wise relevance propagation method was designed to map the abnormalities in the calculation process to the abnormalities of attributes. At the same time, considering that the data set may already contain some useful information, we designed filtering rules for a kind of data set that can be obtained at a low cost, so that the calculation result is presented in a more accurate manner, which should help professionals lock and address intrusion threats more quickly.

scholarly journals Abnormal detection technology of industrial control system based on transfer learning

2022 ◽  
Vol 412 ◽  
pp. 126539
Author(s):  
Weiping Wang ◽  
Chunyang Wang ◽  
Zhen Wang ◽  
Manman Yuan ◽  
Xiong Luo ◽  
...  
Keyword(s):  
Control System ◽  
Transfer Learning ◽  
Industrial Control System ◽  
Industrial Control ◽  
Abnormal Detection ◽  
Detection Technology
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