Computer Network Information Research Articles

Application of Big Data Technology in Network Information Security Issues

In recent years, the rapid development of China s economy and information technology has promoted the application of big data technology in computer information systems. However, there are still some issues in practical applications that need to be overcome. This paper summarizes experiences and studies the current application status and problems of big data technology in computer network information security, hoping to provide assistance for future practical work.

Big data algorithm for computer network information security in the 5G era

Computers play a very important role in today’s life. A large amount of personal information exists in computers, so it is very important to protect the information security on computer networks. The development of information technology has brought a huge impact on human society, and the information security of its computer network has attracted more and more attention. Aiming at the needs of computer network information management in the age of big data, this paper has developed a special computer network information protection system to deal with various threats and constantly improve the protection system. Based on this, the concept and advantages of the 5G network are first expounded, and the management technology of the 5G network is briefly analyzed. Then the information security problems of computer networks in the 5G era are considered, and effective solutions to the information security problems are proposed. Through research and calculation, the new computer network security system can improve network information security by 13.4%.

Характерные особенности современных информационных войн политической направленности

The article analyzes the characteristic features of information wars of a political orientation. Today, information wars are an integral element of the political system, acting as an instrument of political governance. The specificity of information warfare lies primarily in the fact that the fighting takes place in the plane of virtual space. It was revealed that the worldwide information computer network has brought information warfare to a new level, becoming a powerful tool for implementing information attacks. This trend is reflected in the political conflicts that occur within the boundaries of the information field.

Development of an intrusion detection system using mayfly feature selection and artificial neural network algorithms

Protecting the privacy and confidentiality of information and devices in computer networks requires reliable methods of intrusion detection. However, effective intrusion detection is made more difficult by the enormous dimensions of data available in computer networks. To boost intrusion detection classification performance in computer networks, this study developed a feature selection mode for the classification task. The proposed model utilized the Mayfly feature selection algorithm and ANN as the classifiers. The model was also tested without a mayfly algorithm. The model's efficacy was determined through a comparison of its accuracy, specificity, precision, sensitivity, and F1 score. The experimental outcomes revealed that the proposed model is more efficient than existing models based on the performance evaluation and the CIC-IDS 2017 dataset employed in this research. Accuracy scores of 99.94% (using Data+mayfly+ANN) and 90.17% (using Data+ANN) were attained after experimentation. In comparison to existing models, the proposed model yielded better results in terms of accuracy, sensitivity, specificity, and F1-score metrics. The model's sturdiness can be attributed to the use of mayfly techniques, which harness the strength in PSO, GA and FA for selecting optimal feature subsets. The results of this research provide a reliable dimensionality reduction model that may be used in the field of computer networks for intrusion detection and enhancement of security in computer networking environments.

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

Analysis of computer network information security and protection strategy

Analysis of computer network information security and protection strategy

A Practical Study of Big Data Technology in Computer Network Information Security Processing

In recent years, China has witnessed continuous development and progress in its scientific and technological landscape, with widespread utilization of computer networks. Concurrently, issues related to computer network information security, such as information leakage and virus invasions, have become increasingly prominent. Consequently, there is a pressing need for the implementation of effective network security measures. This paper aims to provide a comprehensive summary and analysis of the challenges associated with computer network information security processing. It delves into the core concepts and characteristics of big data technology, exploring its potential as a solution. The study further scrutinizes the application strategy of big data technology in addressing the aforementioned security issues within computer networks. The insights presented in this paper are intended to serve as a valuable reference for individuals involved in the relevant fields, offering guidance on effective approaches to enhance computer network information security through the application of big data technology.

Risk assessment of computer network information using a proposed approach: Fuzzy hierarchical reasoning model based on scientific inversion parallel programming

Abstract Background Computer networks are involved in many fields such as business, education, marketing, government, and tourism in several forms. Technologies related to security protection and improvement of information integrity are used and developed for computer networks intruded on by unauthorized people and help save their confidentiality. Methods To improve the risk identification of computer networks, this manuscript combined a fuzzy hierarchical reasoning model with the scientific inversion parallel programming method to study the risk of computer networks. Moreover, this article defined and analyzed a d-order neighborhood message propagation algorithm. A d-order neighborhood parallel message propagation algorithm using the Gaussian graph model was proposed. Results The risk of the computer network was analyzed using the proposed method resulting in better protection effectiveness. Conclusion The simulations showed that the proposed algorithm could effectively detect risks and improve the security of the computer network.

Criteria of reliability of computer networks and assessment quality of service

A modern computer network counts tens of millions of servers and hundreds of millions of workstations. Network technologies have found widespread use in industry and business, so network reliability has become one of the most pressing problems.
 In general, the reliability of all systems is determined by the reliability of their constituent elements. Different elements have different reliability. In many cases, reliability and reliability distributions are determined empirically.
 If we define the reliability of the system as the possibility of communication between different nodes and workstations, then the reliability of the Internet turns out to be equal to the whole. Unless your workstation is among thousands of nodes, you cannot guarantee the absolute reliability of the network, so it is clear that both definitions are completely unacceptable.
 The selection of criteria for determining the reliability and performance of information computer networks is one of the main problems of information systems

О СОВЕРШЕНСТВОВАНИИ ПРОЦЕССУАЛЬНОГО ПОРЯДКА СОБИРАНИЯ ДОКАЗАТЕЛЬСТВ В КОМПЬЮТЕРНЫХ СЕТЯХ

This article is aimed at identifying such a problematic aspect as the procedural procedure for collect-ing evidentiary information in computer networks. The author considers some previously put forward scientific proposals aimed at resolving problematic issues regarding the conditions and procedure for conducting investigative actions for the purpose of visual perception and research of information placed on local and network electronic media, as well as in computer networks. The definition of compulsory examination of an information system located on electronic media outside the place of the investigative action is given. The list of current legislation and current regulatory legal acts aimed at regulating relations arising from the interaction of preliminary investigation bodies and telecom operators providing connection services to information and communication networks, as well as organizers of the dissemination of information on the Internet is given. Particular attention is paid to the problems and prospects of obtaining such criminally significant information as cookies. Their definition is given; the classification of the main types is given. The necessity of supplementing the com-position of the information to be stored by the organizer of the dissemination of information on the In-ternet for the purpose of preventing and combating crime in the Russian Federation is indicated.

Retracted: Computer Network Information Security Monitoring System Based on Big Data Era

Retracted: Computer Network Information Security Monitoring System Based on Big Data Era

Research on computer network information image data processing based on machine learning

Abstract In this paper, we aim to progress the efficiency and accuracy of information processing and security detection in computer networks by introducing convolutional neural networks in machine learning algorithms that are capable of multi-scaling from the channel attention module and spatial attention module in extracting image information. Global maximum pooling and global averaging are done for the feature maps generated by both modules to get the clearest feature maps by dimensionality reduction. The loss function is used to calculate the feature maps to reduce the data loss generated during data extraction and finally complete the image data processing. To verify the effectiveness of the proposed platform, network images containing different amounts of data are input into the platform, and the accuracy and loss of data extraction are obtained. The results show that the data extraction accuracy of the reduced platform is up to 100%, which is 6% higher than other platforms. The number of data losses in other platforms is more than twice of this paper, while the number of losses in this paper can be controlled within 5. It can be seen that convolutional neural network in machine learning improves the accuracy of data extraction from computer network information images and reduces the loss in data extraction.

Cybersecurity in Business: A Case Study of DiDi

Big data has substantially improved the efficiency of information collection and processing (Fadhil et al., 2021). (Fadhil, S. A., Kadhim, L. E. and Abdurazaq, S. G. (2021) ‘Protection measurements of computer network information security for big data’, Journal of Discrete Mathematical Sciences and Cryptography, Vol. 24, No. 7, pages 1959–1965, doi: 10. 1080/09720529.2021.1959996). Nevertheless, the transparentizing and openization of information could also increase the risk of disclosure of personal information and business secrets, leading to various illegal and criminal activities (Lim et al., 2018). (Lim, S., Woo, J., Lee, J. and Huh, S. -Y. (2018) ‘Consumer valuation of personal information in the age of big data’, Journal of the Association for Information Science and Technology, Vol. 69, No. 1, pages 60–71, doi: 10.1002/asi.23915). This paper adopts qualitative analysis and single-case study to investigate the approaches and outcomes of network information collection. It is found that many e-commerce platforms utilize big data technologies to collect, screen and process customer information. Yet, the collected customer information might be maliciously used by others to infringe on personal privacy, result in property damage and loss, trigger unhealthy market competition, and hinder economic development (Taylor, 2017). ((Taylor, I. (2017) ‘Data collection, counterterrorism and the right to privacy’, Politics, Philosophy & Economics, Vol. 16, No. 3, pages 326–346, doi: 10.1177/ 1470594X17715249). Thus, this paper recommends that the application of big data should have a legal boundary. It needs to be strictly defined and regulated to facilitate its positive role in protecting cybersecurity and promoting fair market competition. Big data, business secret, cybersecurity, data right, e-commerce platform, information processing, legal boundary, market competition, network platform, personal privacy

Retracted: Application of Data Encryption Technology in Computer Network Information Security

Retracted: Application of Data Encryption Technology in Computer Network Information Security

Корпоративне навчання як новий бренд методичної служби в закладі загальної середньої освіти

Methodical work in a modern school is an integral system of interrelated activities based on the achievements of psychological and pedagogical science, advanced pedagogical experience and aimed at improving the professional skills of teachers, developing the creative potential of each teacher in particular and the entire teaching staff in order to increase the effectiveness of the educational process.
 The content of the article reveals the questiona new approach to the organization of methodological work, which is the most important link in the system of continuous training of members of the teaching staff and is aimed at enriching and developing the creative potential of teachers.
 Given the practical implementation of the tasks of the State National Program "Education (Ukraine of the XXI century)," the urgent task is to adapt teachers to educational requirements. An important role in ensuring the reform of education is played by the modernization of scientific and methodological work in an educational institution through the introduction of modern educational, management technologies, stimulating professional growth of personnel, increasing their professional skills, in particular; through the effective application of effective forms and methods of adult learning, tools, computer learning systems and information network interaction.
 A model of the system of organization of methodological work in the institution of general secondary education has been developed. It is determined that methodical work with pedagogical personnel occurs by differentiation of pedagogical potential and requires the presence (or formation) of information and technological competence among pedagogical workers, which is advisable to do through corporate training.
 Therefore, in the present (the emergence and dissemination of a large amount of information), a key feature of the system of methodological work with pedagogical personnel should be the ability to obtain the necessary skills in time to be able to meet immediate educational needs. The article determined that the most effective method in this case is corporate training. The priority of which is the acquisition of relevant knowledge, skills and abilities to increase the efficiency of any institution in general and institutions of general secondary education in particular.

Retracted: Application Research of Data Encryption Technology in Computer Network Information Security

Retracted: Application Research of Data Encryption Technology in Computer Network Information Security

Information security of hospital computer network based on SAE deep neural network

Abstract As the pace of hospital informatization construction continues to accelerate, information network technologies are being used more and more extensively in the medical industry. These advanced technologies make medical businesses more and more dependent on industry information and data, which brings about network system security issues that cannot be ignored. To strengthen the daily operation and management of hospitals, ensure the stable operation of computer systems, and do a good job in protecting the security of hospital computer system network information, this paper designs a risk assessment method for hospital computer network information security based on SAE deep neural network and analyzes the main factors affecting the security of hospital computer system network information. The experimental results prove that the proposed method can effectively improve the reliability of the evaluation results and ensure the accuracy of the evaluation results. According to the obtained information security model, it can effectively guide the construction and application of hospital computer network information systems, optimize the system network, and promote the development of hospital informatization.

Computer network security and information security technology optimization by using Bayesian classification algorithm

Computer network security and information security technology optimization by using Bayesian classification algorithm

Analysis of the dilemma of higher vocational thinking education in China under the background of “Internet+”

Abstract Network culture is a culture based on computer network information technology. With the popularity of “Internet+”, the influence of network culture on college students’ ideological views, behavioral patterns, value orientations and psychological development is also increasing. While Internet culture brings opportunities to higher education ideological and political education, it also makes education work face serious challenges. This paper proposes a collaborative knowledge graph construction method for Civic Education based on Internet + group intelligence. The core of the method is a continuously running loop that contains 3 activities: free exploration, automatic integration, and active feedback. The experimental results show that the knowledge graph fusion algorithm can effectively utilize the structural information of the knowledge graph as well as the semantic information of the nodes to form a high-quality knowledge graph fusion scheme. The collaborative approach based on the “explore-fusion-feedback” loop can improve the scale of group construction of knowledge graphs and the efficiency of individual construction of knowledge graphs, and exhibit better scalability of group scale.

Computer network information security and protection strategies in the era of big data

The Internet has entered the big data era, and as more and more businesses employ big data, cloud computing, the Internet of Things, artificial intelligence, and other technologies, the amount of data on the Internet as a whole has also grown dramatically. While Big Data technology has improved the efficiency of many companies, it has also brought challenges for computer network information security protection technology, including massive data privacy leaks that seriously jeopardize the privacy of Internet users. This paper synthesizes literature review findings proving that computer network information security in the big data era has the characteristics of universality, suddenness, concealment, and intelligence in order to address this issue. It also studies the main network information security technologies, such as network situational awareness, vulnerability scanning, intrusion detection and firewall, and identity authentication. In addition, the paper finds that the current problems of network information security mainly include phishing attacks, computer viruses, ransomware, denial of service attacks, APT attacks and threats from inside the network. Finally, the paper explores a number of protective measures to address existing security issues, including the development of network monitoring and threat intelligence systems, the implementation of access control and authentication technologies, network isolation methods, regular software scanning and updates, and organising internal staff security training. Through this study we are able to fully understand the overall pulse of current computer network information security technology and development trends in the era of Big Data, thus providing a more comprehensive and accurate reference for Big Data-related participants to develop responsive information security protection measures and strategies to provide designation.