Network Security Problems Research Articles

Computer Network Security Technology and Prevention Strategy Analysis

The use of computers has brought convenience to people's work and life, but also caused network security problems. How to identify network security risks and ensure users' personal privacy has become very important. With the continuous development of the current era, social science and economy have achieved rapid development. The integration of Internet intelligence has also brought efficiency and convenience to people's life. However, under this good development background, there are also some potential security problems in computer networks, it is a great threat to the security of the computer network. It is very important to study the development of computer network security technology. based on this, the article will be the computer network security technology of the influencing factors and preventive measures. this requires us to improve our understanding of network information security technology. This paper aims at how to effectively carry out network security technology and seek scientific prevention strategies, hoping to provide strong support for Internet security.

A New Intrusion Detection Algorithm AE-3WD for Industrial Control燦etwork

In this paper, we propose a intrusion detection algorithm based on auto-encoder and three-way decisions (AE-3WD) for industrial control networks, aiming at the security problem of industrial control network. The ideology of deep learning is similar to the idea of intrusion detection. Deep learning is a kind of intelligent algorithm and has the ability of automatically learning. It uses self-learning to enhance the experience and dynamic classification capabilities. We use deep learning to improve the intrusion detection rate and reduce the false alarm rate through learning, a denoising AutoEncoder and three-way decisions intrusion detection method AE-3WD is proposed to improve intrusion detection accuracy. In the processing, deep learning AutoEncoder is used to extract the features of high-dimensional data by combining the coefficient penalty and reconstruction loss function of the encode layer during the training mode. A multi-feature space can be constructed by multiple feature extractions from AutoEncoder, and then a decision for intrusion behavior or normal behavior is made by three-way decisions. NSL-KDD data sets are used to the experiments. The experiment results prove that our proposed method can extract meaningful features and effectively improve the performance of intrusion detection.

Network Security System Design of Big Data Platform in Tai'an of Health Based on IPV9 Technology

Abstract At present, IPv4 is the core of the Internet. When it was designed, security protection was hardly considered. Therefore, the Internet has many security loopholes, which cause information leakage or even breakdown. Compared with IPv4, IPv6 has been improved in terms of security, but IPv6 packets are not encrypted and verified by default, and the problem of network layer being attacked is still unresolved. So, the Internet based ipv6 is still faces the risk of data being monitored and tampered, which cannot effectively prevent malicious attacks. China Decimal Network Standard working group developed the future network system, which adopts the zero-trust security mechanism of verification before communication. Big Data Platform in Tai’an of Health is responsible for the unified management of all medical and health institutions in the platform, and for the management, communication and maintenance of all data. Therefore, the establishment of the network security system of this platform should pay more attention to effective, scientific and comprehensive requirements. In this paper, the Future Network (IPV9) with independent intellectual property rights in China and its encryption technology are introduced, and the network security system of Big Data Platform in Tai'an of Health is designed, and the corresponding simulation test is carried out, which achieves the expected effect. The design of network security system of Big Data Platform in Tai'an of Health based on IPV9 can play a certain role and reference value in solving network security problems in Big Data Platform of Health.

Safe Exploration in Wireless Security: A Safe Reinforcement Learning Algorithm With Hierarchical Structure

Most safe reinforcement learning (RL) algorithms depend on the accurate reward that is rarely available in wireless security applications and suffer from severe performance degradation for the learning agents that have to choose the policy from a large action set. In this paper, we propose a safe RL algorithm, which uses a policy priority-based hierarchical structure to divide each policy into sub-policies with different selection priorities and thus compresses the action set. By applying inter-agent transfer learning to initialize the learning parameters, this algorithm accelerates the initial exploration of the optimal policy. Based on a security criterion that evaluates the risk value, the sub-policy distribution formulation avoids the dangerous sub-policies that cause learning failure such as severe network security problems in wireless security applications, e.g., Internet services interruption. We also propose a deep safe RL and design four deep neural networks in each sub-policy selection to further improve the learning efficiency for the learning agents that support four convolutional neural networks (CNNs): The Q-network evaluates the long-term expected reward of each sub-policy under the current state, and the E-network evaluates the long-term risk value. The target Q and E-networks update the learning parameters of the corresponding CNN to improve the policy exploration stability. As a case study, our proposed safe RL algorithms are implemented in the anti-jamming communication of unmanned aerial vehicles (UAVs) to select the frequency channel and transmit power to the ground node. Experimental results show that our proposed schemes significantly improve the UAV communication performance, save the UAV energy and increase the reward compared with the benchmark against jamming.

WIRELESS SENSOR NETWORK: TOWARDS AN IMPROVEMENT OF SECURITY POLICY

Abstract. The ad hoc network (or MANET, for Mobile Ad hoc NETwork) is a system containing a set of devices that organize themselves, thus forming an autonomous and dynamic network, communicating via radio interface. These devices can be fixed or mobile, no wired infrastructure is available, and so these objects have to dynamically discover their environment.The design of these applications is based on trust between the nodes constituting the network. Unfortunately, when deploying randomly in difficult hostile areas, seeing impossible to monitor, not to mention the uncertainty of the communication channel, the sensor nodes are exposed to all types of attacks and intrusions, which can hinder and prevent the diffusion of the information between the sensor nodes of the network, and influencing its performance.Many approaches have been proposed to solve security problems in wireless networks. The solutions can be mainly classified into two categories: symmetric and asymmetric key management schemes. Indeed it is clear, that the optimal solution in this case is to use symmetric shared key systems.In this paper, the idea of LEAP improved is to apply the same Mechanisms used in LEAP Enhanced to overcome a compromised node and also prevent a compromised base station node while using a multiple base station network, this will, on the one hand, minimize power consumption, and secondly, to replace a base station in the event of a compromise, to ensure the continuity and proper functioning of the network. The evaluation of the proposed solution was carried out using the TOSSIM simulation tool.

A Review of P4 Programmable Data Planes for Network Security

Network attacks show a trend of increased attack intensity, enhanced diversity, and more concealed attack methods, which put forward higher requirements for the performance of network security equipment. Unlike the SDN (software defined network) switch with a fixed-function data plane, switches with programmable data planes can help users realize more network protocols. Programming Protocol-independent Packet Processors (P4) is proposed to define the operations of the data plane and to implement user’s applications, e.g., data center networks, security, or 5G. This paper provides a review of research papers on solving network security problems with P4-based programmable data plane. The work can be organized into two parts. In the first part, the programming language P4, P4 program, architectures, P4 compilers, P4 Runtime, and P4 target are introduced according to the workflow model. The advantages of P4-based programmable switching in solving network security are analyzed. In the second part, the existing network security research papers are divided into four parts according to the perspectives of passive defense, active defense, and combination of multiple technologies. The schemes in each category are compared, and the core ideas and limitations are clarified. In addition, a detailed comparison is made for the research on the performance of P4 targets. Finally, trends and challenges related to the P4-based programmable data plane are discussed.

Survey on security issues of routing and anomaly detection for space information networks

Space information networks is network systems that can receive, transmit, and process spatial information lively. It uses satellites, stratosphere airships, Unmanned Aerial Vehicles, and other platforms as the carrier. It supports high-dynamic, real-time broadband transmission of earth observations and ultra-long-distance, long-delay reliable transmission of deep space exploration. The deeper the network integration, the higher the system’s security concerns and the more likely SINs will be controlled and destroyed in terms of cybersecurity. How to integrate new IT technologies such as artificial intelligence, digital twins, and blockchain to diverse application scenarios of SINs while maintaining SIN cybersecurity will be a long-term critical technical issue. This study is a review of the security issues for space information networks. First, this paper examines space information networks’ security issues and figures out the relationship between the main security threats, services, and mechanisms. Then, this article selects secure routing and anomaly detection from many security technologies to conduct a detailed overview from two perspectives of traditional methods and artificial intelligence. Subsequently, this paper investigates anomaly detection schemes for spatial information networks and proposes a deep learning-based anomaly detection scheme. Finally, we suggest the potential research directions and opening problems of space information network security. Overall, this paper aims to give readers an overview of the newly emerging technologies in space information networks’ security issues and provide inspiration for future exploration.

The Border Attack Defense System is Software-Based

Now the computer has been completely towards the public, the network in daily life is more and more widely used, but at the same time, the potential network security problems are also more and more serious. Some sophisticated computer people in order to make money, crack other personal users or company information, a variety of network attacks one after another. Cyber attack has become an extremely feared existence for ordinary people because of its wide range of attacks, strong attack force and obvious hiding effect, which seriously threatens the security of personal information network. If attacked by this kind of attack, the loss borne by each person or company is immeasurable. In order to maintain network security, the defense system is also improving day by day, and finally presents software. This paper mainly makes a detailed understanding of the border attack and defense system, and analyzes the main reasons and inevitability of the software of the border attack and defense system.

Research on Risk Factors of Fuzzy Evaluation of Network Security Based on Computer Big Data

Under the background of big data, computer technology is widely used in all walks of life, and enterprises need strong technical support. The advent of the era of big data has greatly improved the efficiency of the Internet era, but it has also brought more serious network security problems. In view of the complexity of influencing factors and difficulty in quantifying indicators in network security risk assessment, a risk quantification method based on fuzzy comprehensive evaluation is proposed, and a grading index system of influencing factors for a single risk scenario is established. The enterprise network security risk is divided into five levels, and the enterprise network security risk level is determined according to the evaluation of the expert group. The application example shows that the above algorithm can quantitatively evaluate the dynamic risk of network system and improve the accuracy of network security risk assessment. Finally, aiming at the problems existing in computer network information security, the corresponding countermeasures are put forward. It is hoped that the new key technology of network security risk assessment combined with data application can better realize network security application and protect the privacy of network information.

Development of Computer Network Security Based on Cloud Computing

Cloud computing not only provides convenience for users, but also brings certain information security threats to users. How to effectively protect the user’s information security has become one of the core issues of network security. This paper analyzes the problems and reasons of network security in cloud computing environment, and points out the main ways to improve network security. This paper analyzes the network security problems in the cloud computing environment, and discusses the information security technology in the network. This paper studies the definition, characteristics, classification and core technology of cloud computing security, analyzes the security risk of cloud computing network, and puts forward the cloud computing network security model and security level evaluation method from different angles. Level experiment results show that the network security model in cloud environment is feasible, computing can fully meet the development requirements of the current network information age, and effectively standardize the network security operation environment. The results show that: in 2016, the number of articles related to cloud computing is at least 2653, and in 2020, the number of articles related to cloud computing is at most 6438.

Research on Application of Artificial Intelligence in Network Security Defence

Network security gradually matures with the development of IT technology, and the exponential growth of massive data makes data leakage more common for many reasons. To explore the application of artificial intelligence technology in network security defense. Based on the security problems existing in different network information systems, this paper constructs an intelligent security analysis and management system from the perspective of network security protection, and introduces it into the big data network security platform. In combination with different security protection requirements, the existing network security problems are detected and dealt with. The VLAN routing command is configured to multiple switches to quickly complete multiple sets of network security solutions and implementation, and achieve a more comprehensive and intelligent network security defense.

Feature Extraction Method for Hidden Information in Audio Streams Based on HM-EMD

Using fake audio to spoof the audio devices in the Internet of Things has become an important problem in modern network security. Aiming at the problem of lack of robust features in fake audio detection, an audio streams’ hidden feature extraction method based on a heuristic mask for empirical mode decomposition (HM-EMD) is proposed in this paper. First, using HM-EMD, each signal is decomposed into several monotonic intrinsic mode functions (IMFs). Then, on the basis of IMFs, basic features and hidden information features HCFs of audio streams are constructed, respectively. Finally, a machine learning method is used to classify audio streams based on these features. The experimental results show that hidden information features of audio streams based on HM-EMD can effectively supplement the nonlinear and nonstationary information that traditional features such as mel cepstrum features cannot express and can better realize the representation of hidden acoustic events, which provide a new research idea for fake audio detection.

Application of Computer Network Security Information Encryption Technology

With the continuous development of information technology, computers have been widely used in various fields of society, filled with rich information in the network, network security has been widely concerned. In view of the problem of insufficient network security, we must strengthen the application of security measures, among which information encryption technology is one of the important means to ensure network information security at the present stage. This paper mainly summarizes the information encryption technology, analyzes the factors affecting network security, and puts forward effective protective measures to ensure the security of computer network.

Research on Computer Network Security Problems and Countermeasures

With the continuous development of internet, people cannot live without computers and networks. However, in the process of using network, there are often a lot of security problems. This reduces the user’s sense of experience and threatens the security of users’ personal information. This study discusses the importance of computer network security, the specific types of security problems and several effective countermeasures. This provides a basis for the development of computer network security.

Handoff control strategy of cyber physical systems under dynamic data attack

With the continuous development of Internet technology and Internet of things technology, digital and intelligent industrial system will continue to iterate. At the same time, as the core technology of the new generation of industrial system, cyber physical systems has also received more and more attention. At present, there are network security problems such as virus intrusion, denial of service and so on in the cyber physical systems, and the corresponding dynamic data attack will damage the cyber physical systems. Based on this, this paper will start with the information physical switching control theory under the dynamic data attack, and first establish the relevant mathematical model of the cyber physical systems for analysis, so as to realize the stability of the cyber physical system and the sensitivity of the handoff strategy so as to realize the stability of the cyber physical systems The sensitivity of switching strategy. In order to achieve the stability of the cyber physical systems under dynamic data attack, based on the control initiative related theorem, an innovative steady-state correction algorithm of the cyber physical systems is proposed, so that the system can achieve good control performance under dynamic data attack. The simulation results show that the proposed control strategy is effective.

Research on Network Intrusion Detection Method Based on Deep Learning Algorithm

Information security is very important in enterprises. Under the tide of modern network informationization, especially intrusion detection is facing great challenges. The rise of technologies such as big data and artificial intelligence, on the one hand, helps to strengthen information security, on the other hand, it also brings great challenges to information security. Everything has two sides, and the Internet is no exception. While the network has brought us a richer and faster life, the problem of network security has become increasingly prominent, and network security risks pose new challenges to the fields of politics, economy, culture, national defense, ecology and society. The active defense strategy using intrusion detection technology can actively discover attacks when they occur or attempt to attack, realize real-time response, and provide real-time protection for network systems. This paper starts from the field of intrusion detection and combines deep learning technology to design an efficient and intelligent intrusion detection model which can be used in the field of network intrusion detection.

Computer Network Security under the Cloud Computing Technology Environment

The development of network technology has changed the traditional network application mode to coordinate all kinds of data and resources effectively. It brings about the improvement of computer computing ability, data processing ability and storage ability, and offers users a new and optimized usage experience by improving the ability of computer network service. However, the construction of cloud computing technology environment also causes people to worry about the network security, and the problem of computer network security under cloud computing technology environment can not be underestimated. The top priority is to speed up the research and development of defense technology, improve the risk response system, consciously enhance the awareness of security protection, and be answerable for dealing with network risk with multi-pronged measures. This work mainly discussed the problems of computer network security under cloud computing technology environment from aspects of encryption technology, authorized accessing, network monitoring, and consciousness awakening, expecting to provide guidance and reference for computer network security response under the background of cloud computing.

Analysis on the Change of Big Data and Computer Network Communication Technology Based on Multi-platform

Since the 20th century, information and network technology, mainly represented by microelectronics, computer communication and network technology, has progressed and developed rapidly, and its dissemination and application have had a significant impact on economic development and social transformation. Among them, modern computer communication is an emerging discipline that effectively combines modern computer technology and communication technology. It has developed rapidly after experiencing the information revolution, which has greatly changed the daily work and lifestyle of people in modern society, and the changes in communication have also changed. After entering the new era, the conversion stage from analog signal to digitization to communication signal has basically ended. However, in the field of modern digital communication, there is still a lot of room for the advancement and development of electronic computer technology. Many new technologies and new technologies are emerging in an endless stream, which also provides ample room for future development of the industry. This article analyzes the transformation of computer network communication technology based on multi-platform data. First, use literature research methods to analyze the advantages of computer network communication technology in the era of big data. And summarize the problems of computer network general technology, and then use questionnaires based on big data platform to investigate the impact of computer network communication technology changes on people and the failure of computer network communication in life. The result shows that the video upload fails. The occurrence is very high. About 60% of people have experienced video upload failures. There are relatively few failures in hacking and image upload failures. This shows that the solution to the information network security problem in China is still possible, but the video high incidence of upload failures indicates that the speed of computer network communication needs to be strengthened. The direct impact of the reform of computer network technology is that people have more frequent contacts. About 50% of people have more frequent contacts with family and friends after the reform of computer network technology.

Perancangan Security Network Intrusion Prevention System Pada PDTI Universitas Islam Raden Rahmat Malang

Security is very main in computer networks, where many devices are connected to each other to interact and exchange data without limits. Network security is also a very important issue to prioritize, one of which is to use an intrusion prevention system. At PDTI UNIRA there are often network security problems, one of which is that during the test season, the server experiences many intrusion problems. The purpose of this research is to develop a social science system based on the analysis at PDTI of Raden Rahmat Islamic University Malang. This research method uses a computer security development approach, namely the Intrusion Prevention System (IPS), by combining firewall engineering methods and Intrusion-Detection System (IDS). The result of this research is a technology that can be used to prevent attacks that will enter the local network checking and recording all data packets and recognizing sensor packets, when the attack has been identified, IPS will deny access (block) and record (log) all data packets. identified. So IPS acts as a firewall that will allow and block combined with IDS that can detect packets in detail. With a network security system, the Unira PDTI server is safer and can avoid intrusion.

Deep Learning Approaches for Intrusion Detection

Recently, computer networks faced a big challenge, which is that various malicious attacks are growing daily. Intrusion detection is one of the leading research problems in network and computer security. This paper investigates and presents Deep Learning (DL) techniques for improving the Intrusion Detection System (IDS). Moreover, it provides a detailed comparison with evaluating performance, deep learning algorithms for detecting attacks, feature learning, and datasets used to identify the advantages of employing in enhancing network intrusion detection.