A W-EAP Algorithm for IEC 61850 Protocol against DoS/Replay Attack

Substation automation system uses IEC 61850 protocol for the data transmission between different equipment manufacturers. However, the IEC 61850 protocol lacks an authentication security mechanism, which will make the communication face four threats: eavesdropping, interception, forgery, and alteration. In order to verify the IEC 61850 protocol communication problems, we used the simulation software to build the main operating equipment in the IEC 61850 network environment of the communication system. We verified IEC 61850 transmission protocol security defects, under DoS attack and Reply attack. In order to enhance security agreement, an improved algorithm was proposed based on identity authentication (W-EAP, Whitelist Based ECC & AES Protocol). Experimental results showed that the method can enhance the ability to resist attacks.

Research on DoS Attack Detection Method of Modbus TCP in OpenPLC

With the development of new information technologies such as cloud computing, Internet of Things, and mobile Internet of Things, Industry 4.0, Smart Manufacturing and Made in China 2025 have been proposed as the main content of the development of the next industrial revolution. In order to realize these projects with the common characteristics of intelligence, service, and green, a new manufacturing model, digital twin, is proposed, which combines the digital twin with industrial systems, that is, the industrial control virtualization system. However, due to the frequent occurrence of industrial control system security incidents in recent years, the industrial control virtualization system is vulnerable to attacks. The industrial control system is huge and cumbersome. Once attacked, it will cause consequences that affect the whole body. In response to this problem, this article carried out a research on DoS attack detection methods for Modbus TCP in OpenPLC, using OpenPLC as a tool for industrial control system virtualization, building a digital twin system with Raspberry Pi, and launching DoS attacks on the system, combined with Snort Intrusion detection is carried out, and the experimental results show that the built digital twin system can detect DoS attacks in OpenPLC.

AES RSA-SM2 Algorithm against Man-in-the-Middle Attack in IEC 60870-5-104 Protocol

The IEC60870-5-104 protocol lacks an integrated authentication mechanism during plaintext transmission, and is vulnerable to security threats, monitoring, tampering, or cutting off communication connections. In order to verify the security problems of 104 protocol, the 104 master-slave communication implemented DoS attacks, ARP spoofing and Ettercap packet filtering and other man-in-the-middle attacks. DoS attacks may damage the network functions of the 104 communication host, resulting in communication interruption. ARP spoofing damaged the data privacy of the 104 protocol, and Ettercap packet filtering cut off the communication connection between the master and the slave. In order to resist the man-in-the-middle attack, the AES and RSA hybrid encryption signature algorithm and the national secret SM2 elliptic curve algorithm are proposed. AES and RSA hybrid encryption increases the security strength of communication data and realizes identity authentication. The digital signature implemented by the SM2 algorithm can realize identity verification, ensure that the data has not been tampered with, and can ensure the integrity of the data. Both of them improve the communication security of the 104 protocol.

Analysis on the Effect of Government Investment on Private Investment in Western China——Take Province A as an Example

Since China began reforming and opening up its economy,and especially since the launch of development projects in western China,province A has attracted an increasing amount of investment,which is the main driving force for provincial economic growth.Hence,this study uses a state space model to examine how government investment has affected economic growth in province A in western China,and explains whether there is a crowding-in effect or a crowding-out effect of local government investment on private investment.The findings indicate that both government and private investments have a positive,stimulating influence on economic growth in province A,with the latter being more impactful than the former.Productive and non-productive investments have different effects on province A’s economic growth.From the perspective of the trajectory of government investment elasticity,the elasticity of government and private investments in province A presents a very large spatio-temporal change.That is,from 1994 to 2009,government investment in province A had a crowding-in effect on private investment,but from 2010 to 2017,a crowding-out effect was observed.

When liver disease diagnosis encounters deep learning:Analysis,challenges,and prospects

The liver is the second-largest organ in the human body and is essential for digesting food and removing toxic substances.Viruses,obesity,alcohol use,and other factors can damage the liver and cause liver disease.The diagnosis of liver disease used to depend on the clinical experience of doctors,which made it subjective,difficult,and time-consuming.Deep learning has made breakthroughs in various fields;thus,there is a growing interest in using deep learning methods to solve problems in liver research to assist doctors in diagnosis and treatment.In this paper,we provide an overview of deep learning in liver research using 139 papers from the last 5 years.We also show the relationship between data modalities,liver topics,and applications in liver research using Sankey diagrams and summarize the deep learning methods used for each liver topic,in addition to the relations and trends between these methods.Finally,we discuss the challenges of and expectations for deep learning in liver research.

High-resolution Load Profile Clustering Approach Based on Dynamic Largest Triangle Three Buckets and Multiscale Dynamic Warping Path Under Limited Warping Path Length

With the popularity of smart meters and the growing availability of high-resolution load data, the research on the dynamics of electricity consumption at finely resolved timescales has become increasingly popular. Many existing algorithms underperform when clustering load profiles contain a large number of feature points. In addition, it is difficult to accurately describe the similarity of profile shapes when load sequences have large fluctuations, leading to inaccurate clustering results. To this end, this paper proposes a high-resolution load profile clustering approach based on dynamic largest triangle three buckets(LTTBs) and multiscale dynamic time warping under limited warping path length(LDTW). Dynamic LTTB is a novel dimensionality reduction algorithm based on LTTB. New sequences are constructed by dynamically dividing the intervals of significant feature points. The extraction of fluctuation characteristics is optimized. New curves with more concentrated features will be applied to the subsequent clustering. The proposed multiscale LDTW is used to generate a similarity matrix for spectral clustering, providing a more comprehensive and flexible matching method to characterize the similarity of load profiles. Thus, the clustering effect of a high-resolution load profile is improved. The proposed approach has been applied to multiple datasets. Experiment results demonstrate that the proposed approach significantly improves the Davies-Bouldin indicator(DBI) and validity index(VI). Therefore, better similarity and accuracy can be achieved using high-resolution load profile clustering.