Development Of Computer Networks Research Articles

EFFECTIVENESS OF CLASSIFICATION OF COMPUTER NETWORK TRAFFIC ANALYSIS APPLICATIONS USING MACHINE LEARNING METHODS

The article considers the relevance of network traffic research, which is explained by the introduction of computer networks into the life of every person. The rapid development of computer networks has caused increased attention to issues of quality and reliability of their work. The study of computer network traffic analysis is relevant for ensuring the quality of wired and wireless communication, information resources and information search. The study of network traffic indicates the need for its classification to display network data into traffic classes and application types. It is advisable to use machine learning methods, which facilitates the adaptation of the system to constantly changing Internet resources, taking into account the specifics of network traffic. Network traffic analysis indicates that to successfully classify network traffic, all traffic passing through the network must be stored or processed. It was determined that the classification of network traffic is an important task in the field of computer networks. The purpose of network traffic classification is to map the flow of network data into specific application types or traffic classes. An overview of network traffic classification methods was conducted. The results of a comparison of modern approaches to the classification of network traffic are given. Despite the range of methods, the classification of network traffic is still at the stage of development. It should be noted that modern methods, in particular based on machine learning, prove effective results.

Covert Channel Detection: Machine Learning Approaches

The advanced development of computer networks and communication technologies has made covert communications easier to construct, faster, undetectable and more secure than ever. A covert channel is a path through which secret messages can be leaked by violating a system security policy. The detection of such dangerous, unwatchable, and hidden threats is still one of the most challenging aspects. This threat exploits methods that are not dedicated to communication purposes, meaning that traditional security measures fail to detect its existence. This review has introduced a brief introduction of covert channel definitions, types and developments, with a particular focus on detection techniques using machine learning (ML) approaches. It provides a thorough review of the most common covert channels and ML techniques that are used to counter them, as well as addressing their achievements and limitations. In addition, this paper introduces a comparative experimental study for some common ML approaches that are commonly used in this field. Accordingly, the performance of these classifiers was evaluated and reported. The paper concludes that our information is still at risk, nothing is said to be secured and more work on the detection of covert channels is required.

Introduction to the Role of Computer Networks in Promoting the Development of Human Society

Computer network applications are growing in popularity and coverage as a result of the rapid development of computer network technology, which significantly supports the high-quality growth of human civilization and the ongoing improvement of people's living standards. This paper provides an overview of the history of computer network development and current applications, analyzes the effects of computer networks on human economic, political, and cultural life, and suggests additional application ideas that are optimized in conjunction with future development trends, as well as corresponding improvement countermeasures for adverse effects.

Retraction Note: Reliability of variable slope system and human motion image detection based on Markov chain

With the continuous development of computer networks and the continuous popularization of computer network technology, image detection technology has gained a lot of room for development with the help of the development of image processing technology, and has also been greatly improved in a period of development. When people carry out geotechnical engineering construction, the stability of the slope is related to the safety and construction effect of the entire project. In the specific operation process, researchers usually use appropriate calculation methods to calculate various parameters in engineering construction, and use calculations to specifically determine the stability of highway slopes. In order to improve the safety of geotechnical engineering construction and the stability of highway slopes, this article selects the parameters involved in the slope stability analysis method for analysis, and establishes an equation for reliability analysis during the analysis. By comparing the analysis results of other methods, the researchers believe that the limit equation set in this article can improve the reliability of slope stability analysis. This article also designs a method of human motion image detection, which specifically studies the human motion posture, and uses the characteristics of the skeleton point image and the Euclidean distance to accurately recognize the human motion.

Retraction Note: Development of an abnormal ocean circulation and Japanese visualization teaching system based on the Internet of Things

Today, China’s communications industry is developing rapidly, and Internet of Things (IoT) technology is also widely used in various industries. In view of the rapid growth of Internet of Things users and the ever-increasing demand for intelligence and IT, operators’ customer awareness and the follow-up business assurance function of network application services are facing major challenges. It also observes and studies ocean anomalous circulations at different times, as well as key areas where anomalies occur and evolve. The ocean observation network established by the Institute of Oceanology of the Chinese Academy of Sciences (IOCAS) has deployed more than 20 sets of deep-sea diving markers in the junction area of the Yap–Mariana trenches at 130°E, 140°E, and 142°E. This observation network provides the evolution of sea temperature, salinity, and ocean currents related to recent ENSO events and effectively supplements the shortcomings of on-site observation of ENSO events. With the development of science and technology and the development of computer networks, distance learning has gradually shown its potential advantages. It makes Japanese teaching easier. Due to the popularity of Japanese and the continuous enrichment of Japanese teaching content, it can also continuously update and improve its functions, which can effectively solve the problem of overload. The visualization system is the product of time progress and educational renewal, and it helps to improve the teaching effect of Japanese lessons. It includes new teaching methods and diversified educational resources. With the support of modern educational technology, it is easily recognized by teachers and students.

Design and implementation of a general SQL parser

With the rapid development of computer network, the information security of database becomes more and more important. In database security protection, SQL statements need to be parsed and reconstructed. However, the database audit products on the market lack accurate analysis of SQL statements. Therefore, this paper constructs an SQL parser from four aspects: lexical analysis, syntax analysis, SQL spanning tree optimization and error detection.

Survey on Deep Learning Based Intrusion Detection System

Development of computer network has changed human lives in many ways. Currently, everyone is connected to each other from everywhere. Information can be accessed easily. This massive development has to be followed by good security system. Intrusion Detection System is important device in network security which capable of monitoring hardware and software in computer network. Many researchers have developed Intrusion Detection System continuously and have faced many challenges, for instance: low detection of accuracy, emergence of new types malicious traffic and error detection rate. Researchers have tried to overcome these problems in many ways, one of them is using Deep Learning which is a branch of Machine Learning for developing Intrusion Detection System and it will be discussed in this paper. Machine Learning itself is a branch of Artificial Intelligence which is growing rapidly in the moment. Several researches have showed that Machine Learning and Deep Learning provide very promising results for developing Intrusion Detection System. This paper will present an overview about Intrusion Detection System in general, Deep Learning model which is often used by researchers, available datasets and challenges which will be faced ahead by researchers

From Unknown to Similar: Unknown Protocol Syntax Analysis for Network Flows in IoT

Internet of Things (IoT) is the development and extension of computer, Internet, and mobile communication network and other related technologies, and in the new era of development, it increasingly shows its important role. To play the role of the Internet of Things, it is especially important to strengthen the network communication information security system construction, which is an important foundation for the Internet of Things business relying on Internet technology. Therefore, the communication protocol between IoT devices is a point that cannot be ignored, especially in recent years; the emergence of a large number of botnet and malicious communication has seriously threatened the communication security between connected devices. Therefore, it is necessary to identify these unknown protocols by reverse analysis. Although the development of protocol analysis technology has been quite mature, it is impossible to identify and analyze the unknown protocols of pure bitstreams with zero a priori knowledge using existing protocol analysis tools. In this paper, we make improvements to the existing protocol analysis algorithm, summarize and learn from the experience and knowledge of our predecessors, improve the algorithm ideas based on the Apriori algorithm idea, and perform feature string finding under the idea of composite features of CFI (Combined Frequent Items) algorithm. The advantages of existing algorithm ideas are combined together to finally propose a more efficient OFS (Optimal Feature Strings) algorithm with better performance in the face of bitstream protocol feature extraction problems.

Pengujian QoS Pada Implementasi SDN Berbasis Mininet dan OpenDaylight Menggunakan Topologi Tree

The development of information technology and computer network from time to time is increasing along with the increase in user needs for both from the business, education, industrial, to data security side. Data of network traffic that is getting denser in communication and data exchange between users on computer networks can become a problem when using conventional computer network technology. For that, it needs a new technology that is implemented in computer networks, along with the measurement of Quality of Service (QoS) in it. Software-Defined Networking (SDN) is a solution for this, where the stages of network design, management and implementation, separate the data plane and the control plane. In this research, the implementation of SDN was carried out in the form of a simulation using both of Mininet and OpenDaylight with a Tree Topology, then the QoS measurements were carried out in it. The results of testing and measuring QoS on SDN simulations with Tree topology using Mininet and OpenDaylight, showed a Jitter value of 0.425 ms, a Packet Loss value of 0.266%, a Bandwith value of 9.3925 Mbps, a UDP Throughput value of 2.348 bits/sec, and a TCPThroughput value of 2.335 bits/sec.

Information Security of New Media Art Platform of Distributed System Based on Blockchain Technology

New media art is different from ready-made art, installation art, body art, and land art. New media art is a new art subject category with “optical” media and electronic media as the basic language. And, because of the continuous development of computer networks, distributed database management systems are becoming more and more popular. This article aims to study the information security control problem in the distributed new media system. Through comprehensive access control, reliable support, and many-to-many random mutual encryption, it solves the security requirements of supporting mobile computing in a distributed network environment, communication, and hierarchical grouping. Group key management and other issues have studied some key security technologies for building secure distributed information systems. This article proposes covering the behavior-based access control model ABAC (operation-based access control model), the architecture of the new Trusted Platform Module, the architecture of multithreaded crypto chips, and their service methods, as well as distributed information systems and key management solutions. Approximately obeying the chi-square distribution with 2 degrees of freedom, when the significance level is taken as 5%, the chi-square value for the skin is 5.99. Different initial values are selected for the chaotic sequence, 200 groups of chaotic sequences with a length of 2000 are selected for sequence inspection, and the pass rate is 97.5%. It can be seen that the autocorrelation and cross-correlation characteristics of the improved spatiotemporal chaotic sequence are still relatively ideal, so the usability of the platform is relatively high.

Research on Application Technology of Computer Communication and Network Development Based on Data Mining Technology

With the development of computer technology and internet communication, every country in the world began to implement information management, and applied technical means to upgrade the development scale of social industry, so as to promote the development of national economy in an all-round way. Computers break the limitation of people’s spatial communication, can give full play to the role of network resource sharing, and contribute to the high-speed processing of information. Scientific and rational application of computers can quickly transmit data, which plays an important role in promoting China’s economic development. With the advent of the Internet era, the rapid development of information technology has provided convenience for people’s lives and greatly improved their comprehensive national strength. With the development of digital science, computers and networks are widely used. The development of computer communication and network has been widely used in various fields. From the perspective of technology research and development, this paper explores and analyzes the application and function coordination of computer and network based on data mining technology.

Transmission Quality Classification with Use of Fusion of Neural Network and Genetic Algorithm in Pay&Require Multi-Agent Managed Network.

Modern computer systems practically cannot function without a computer network. New concepts of data transmission are emerging, e.g., programmable networks. However, the development of computer networks entails the need for development in one more aspect, i.e., the quality of the data transmission through the network. The data transmission quality can be described using parameters, i.e., delay, bandwidth, packet loss ratio and jitter. On the basis of the obtained values, specialists are able to state how measured parameters impact on the overall quality of the provided service. Unfortunately, for a non-expert user, understanding of these parameters can be too complex. Hence, the problem of translation of the parameters describing the transmission quality appears understandable to the user. This article presents the concept of using Machine Learning (ML) to solve the above-mentioned problem, i.e., a dynamic classification of the measured parameters describing the transmission quality in a certain scale. Thanks to this approach, describing the quality will become less complex and more understandable for the user. To date, some studies have been conducted. Therefore, it was decided to use different approaches, i.e., fusion of a neural network (NN) and a genetic algorithm (GA). GA’s were choosen for the selection of weights replacing the classic gradient descent algorithm. For learning purposes, 100 samples were obtained, each of which was described by four features and the label, which describes the quality. In the reasearch carried out so far, single classifiers and ensemble learning have been used. The current result compared to the previous ones is better. A relatively high quality of the classification was obtained when we have used 10-fold stratified cross-validation, i.e., SEN = 95% (overall accuracy). The incorrect classification was 5/100, which is a better result compared to previous studies.

Discuss the Security Countermeasures and Data Protection of Library Computer Network

With the development of computer networks, the management and operation of the library are gradually becoming networked. And the network management model has greatly improved the management efficiency of the library. Of course, the computer network also makes the library’s data have hidden dangers. This paper mainly analyzes the library computer network security problem and the improvement measures of the library computer network security problem.

Personalized recommendation algorithm based on online comment sentiment analysis

Artificial intelligence is one of the many branches of computer science. With the continuous development of information technology and computer networks, artificial intelligence technology has also received tremendous support and rapid development. In the computer field, recommendation systems can be said to be the most extensive and successful application of artificial intelligence technology. This paper focuses on the problems of cold start and low recommendation accuracy caused by sparse rating data in traditional recommendation systems, proposes a personalized recommendation algorithm based on online comment sentiment analysis. The algorithm uses feature-level sentiment analysis to mine user preference information implicit in comments, and finally implements recommendations based on user ratings and preference information. Experiments show that the algorithm proposed in this paper can effectively make up for the shortcomings of traditional collaborative filtering recommendation algorithms, and is of great help in improving user cold start and the quality of recommendation results.

Data Transmission Security in Computer Network Communication

In recent years, computer network communication technology has made considerable progress and development, and its scale has now covered all aspects of society and people’s lives. However, while computer network technology promotes social development and improves the convenience of people’s lives, there are still many security problems, especially the difficulty of ensuring the security of user data, which has become a prominent problem in the further development and improvement of communication technology. This article takes the network communication security technology as an entry point, and analyzes its technical types with the aid of data encryption technology, and then analyzes and studies its security in computer network communication data transmission according to the specific points proposed. Through the substantial technical analysis of the computer network security system, the possibility of the system being attacked can be reduced to a certain extent, and the security of network data can be improved. Through the analysis of the integrity of the network system, the overall framework of a distributed network security early warning system based on the network is established, and various structures of the system are analyzed. The network load analysis module is responsible for using key performance index data, such as user traffic, number of users and wireless utilization, and analyzes and classifies the network cell load by combining the partial least square method and BP neural network, so that the key cell performance analysis module is mainly Analyze key performance index data of key communities, obtain early warning thresholds through clustering algorithms, and implement a dynamic early warning system to provide guidance for network planning and mining in key small areas. The database module is responsible for storing all performance data and performance analysis results; the performance query module is responsible for querying and analyzing performance data and static warnings, and presents them to users in the form of text and graphics. Experimental research results show that in this information age, the development of computer networks plays a very important role in the development of our country. Computer network operators make full use of cluster analysis, data mining, encryption algorithms, and early warning systems to conduct research to fully improve the security performance of data in network communications.

Design of Computer Network Security Defense System Based on Big Data

The era of big data promotes the development of computer network, which plays a very important role. Big data can improve people’s life and work enthusiasm with high quality, and further sublimate the standard of the masses. Because of the openness of computer network, it always leads to unnecessary security problems. Therefore, in order to apply the computer network on a large scale and avoid the information leakage caused by the network, this paper proposes the research on the design of computer network security defense system based on the background of big data. First of all, the importance of computer network security is discussed; secondly, the types of network security attacks are discussed, and the computer network security defense system is built by using multi angle and active security defense strategy to maintain the safe operation of the network; then, the risk algorithm is analyzed, and the risk of the whole computer network can be estimated by setting the weight according to the importance of the obtained resources So as to formulate reasonable safety measures. Finally, through the system test, the system has good analysis ability and defense ability, and has outstanding effect in computer network defense.

Research on Landscape Design Assistant System Based on Artificial Intelligence and Information Technology

In addition to creativity, modern landscape design also needs some auxiliary tools to predict the design effect, so as to ensure the design effect before the completion of the landscape. With the development of computer network and electronic information technology, human society has entered the information age, and artificial intelligence technology has been applied to all walks of life. With the continuous development of artificial intelligence, artificial intelligence has existed in all aspects of our lives and has a great impact on our lives. At the same time, through the achievements in recent years, artificial intelligence gradually affects other fields such as design. Therefore, combined with the current situation of landscape design auxiliary system in China, this paper introduces artificial intelligence and information technology into it, and makes the landscape design auxiliary system get further development with the help of artificial intelligence and information technology. This paper first introduces artificial intelligence, analyzes the advantages and development trend of automatic informatization of landscape design auxiliary system, and finally discusses the application of artificial intelligence technology in landscape design auxiliary system.

Analysis of Campus Computer Network Management and Security Technology Based on the Status Quo of Modern Network

At present, with the comprehensive improvement of modern computer science and network literacy, people are increasingly demanding the quality of their lives and related rationality. Slowly, we will gradually find that the computer has now become an important unit in our lives[1]. It seems that without the support of computers, our lives cannot continue. It is precisely because of the development and application of computer networks that the current network security and management measures of some campuses in our country cannot keep up with the upgrading of computer technology. This situation will also lead to loopholes in computer network management and security. In a nutshell, computer network technology unites the space and time of our lives. It is an innovative process in the network age. However, we still need to pay attention to the security management of some campus networks and the enhancement of information technology.

Strengthen the Application Research of Computer Network Management Technology Innovation

With the computer network technology occupying an increasingly important position and role in our daily life, study and work, how to strengthen the computer network management technology and innovative application of computer network management technology has become an urgent problem in the development and application of computer network. In order to strengthen the application effect of computer network management technology innovation, this paper first introduces the application of computer network management technology, and then analyses the innovative application ways of computer network management technology.

Research on the Relationship between Computer Network and Economic Development in Information Environment

In the past two centuries, computer technology has entered a period of rapid development. Through the continuous efforts of researchers and engineers, computer technology has been involved in all aspects of people’s lives. In the economic aspect, computer technology, with its unique characteristics, has brought new opportunities as well as challenges to the development of China’s economy. But on the whole, computer technology has played a role in promoting economic development. Enterprises should actively apply this technology to the operation of the company to form a new company in the information age.