Electric Power Information Network Research Articles

Intrusion Detection Method of Electric Power Information Network in Cloud Computing Environment

With the widespread application of power grid systems, the information security problems faced by power grids have become more obvious. Various internal and external intrusion attacks that occur frequently have become an important issue affecting the normal operation of power generation and operations. The purpose of this paper is to study the intrusion detection method of electric power information(PI) network in the cloud computing environment. With the help of the cloud platform’s ability to process big data, and based on the analysis of the PI network structure, a DBN optimized BP network algorithm is proposed, and the optimized BP neural network is used as a runtime classification program. Experimental results show that MR-DBN-BP has a detection rate of 96.7% for intrusion detection of PI networks, which can effectively detect intrusions and effectively protect the power dispatch system network.

Intrusion Detection in Power Information Network Based on Deep Learning and Cloud Computing

With the electric power information network system has been popularized to all aspects of life, and its accompanying problems also come one after another, that is, its internal and external invasion ways are diversified, then the information security problems will affect the national econo-my, infrastructure and many other livelihood issues. On the one hand, the information security of power network needs the general characteristics of computer information security, while considering the characteristics of high security. According to the structure of power information network, this paper proposes an intrusion detection model to detect power information network, which uses both deep learning theory and cloud computing platform. This model not only uses parallel anomaly de-tection and misuse detection methods, but also can deal with the problem that a single misuse detec-tion model can't detect new attack variants. At the same time, it can capture a large number of data flows of power information network, learn and extract the essential characteristics of data flows through the deep feature learning and extraction ability of deep learning, and quickly and accurate-ly detect through the platform Invasion. Based on the analysis of all kinds of intrusion behaviors in power information network, this paper proposes a data extraction and analysis method based on Hadoop, which improves the accuracy of intrusion detection by analyzing massive captured data flow packets and generating characterization data. At the same time, considering the important factors affecting the detection of power information network intrusion feature selection, we study the auto-matic encoder algorithm using spark platform. According to the experimental results, it is found that this method can improve the feature selection of power intrusion detection system.

Information Hiding Technology in Power System Network Security

Since the beginning of the 21st century, with the popularization and application of electronic information technology in the power system, the power system information network security has begun to attract the attention of all walks of life, especially the power enterprises. To ensure the safety of electric power information network is not only the need to ensure the safety of industrial production and residents’ daily electricity consumption, but also the internal demand to ensure the stability, development and prosperity of national economy. In the electric power industry, the information security of the electric power system is directly related to the production, operation, management and operation of the electric power enterprises. When these information data are illegally violated, it will bring adverse effects to the electric power enterprises. It can be seen from this paper that the network security of the telecommunications industry accounts for a large proportion of 18.7%. Therefore, information security is the important protection content of power enterprise network security. The emergence of information hiding technology, a good realization of the power network information security protection, this paper will be information hiding technology as the focus of research, analysis of its application in the power network security.

A Model of Trusted Network for Electric Power Information Network

A Model of Trusted Network for Electric Power Information Network

SPA Comprehensive Evaluation Model and its Application in the Risk Assessment of Electric Power Information Network

To enhance the electric power information network’s defensive capability for all kinds of security threats, this paper builds a risk assessment model for information network based on the Set Pair Analysis (SPA) comprehensive evaluation. On the basis of SPA theory, the information network’s index and the index of ISO/IEC27005 were formed as a set pair. The model introduced the improved AHP to determine the weight of each index, and extended the Spa’s three-Yuan connection degree to five-Yuan, which considered synthetically to the risk’s certain and uncertain factors. By calculating the connection degree, it can determine the risk value and level. Set pair situation was used to discuss the risk development trend. From practical calculation and the comparison with other assessment algorithm, the model appears simple and reasonable, and the calculation is objective and stable.