An Implementation of NIC Controller Integrated with Security Protection Module

As the cybersecurity situation continues to get tougher, more and more attackers are beginning to place their attention on power system networks, and the struggle between various countries is shifting from the real world to cyberspace. Power system network security protection is crucial. Humans have become inseparable from electricity, so it is vital to ensure power security. Whether for political or war purposes, many attacks related to power systems have occurred throughout history, resulting in extremely serious consequences and extremely high property damage. And power systems require special protection due to their high speed, high energy, and high-risk characteristics. In this paper, we analyze past network attacks on electric power systems, summarize common network attacks, analyze common network security protection means in the industry, dig into the progress of network security protection research on the electric power system, explore how traditional network security protection means including firewall, antivirus software, intrusion detection, and honeypot technology are applied on the electric power system.

With the rapid development of Internet technology, computer has become an indispensable part of modern society. However, with the popularization of computer technology, the problem of network security is becoming increasingly prominent. In recent years, China's network security incidents occur frequently. As a means of attack, computer deception has seriously threatened national information security, social stability and people's life. Therefore, it is of great practical significance to study the role of computer deception in network security. Its purpose is to mislead and deceive users or systems by various means to achieve the purpose of illegally obtaining information, damaging the stability of the system or carrying out other illegal activities. Based on this, this paper aims to explore the role of computer deception in network security. Firstly, the concept, content and present situation of computer network security are expounded, and then the necessity of computer network security management and protection is analyzed. Secondly, the related technology of computer deception is introduced. Finally, the application of computer spoofing in network security is studied, and the effectiveness of computer spoofing in preventing and detecting network attacks is revealed. In addition, the ethical issues of computer deception and its potential in future cybersecurity strategies are discussed. Research shows that computer deception can not only enhance the defense mechanism, but also improve the organization's cognition and response ability to network threats, and become an indispensable security strategy. By evaluating current technologies and methods, this paper provides practical recommendations for researchers and practitioners to effectively use computer spoofing techniques to improve network security.

Digital technologies have expanded the reach of financial services to end-users, improved efficiency and driven global financial innovation to a new level. It has created new directions and opportunities for the transformation and development of the financial industry, but at the same time it has also brought new problems of network security management. In this paper, we study the cybersecurity issues of the financial industry in the context of emerging technologies. The results find that the high-benefit, regulated and high-risk characteristics of the financial sector have led to the prominence of financial data security issues, a significant increase in cyber attacks and more insidious cyber fraud in the financial sector. To this end, it is proposed to implement the network security ecological assessment system as soon as possible, to conduct regular network security attack and defense drills, to strengthen the application of technology in network security, to focus on key areas to carry out publicity activities and other protective measures to build a solid financial network security “firewall”.KeywordsEmerging technologiesNetwork securityProtectionFinancial industry

With the rapid development of information technology and the advancement of smart city construction, urban management and services increasingly rely on networked intelligent systems. However, this highly interconnected network environment has also brought numerous network security challenges to smart cities. Smart cities involve a large number of Internet of Things (IoT) devices, big data platforms, cloud computing technologies, and smart infrastructure, making network security problems more complex and severe. This paper analyzes the composition and development trends of smart cities, explores the main security risks currently faced, and focuses on the security risks in key areas such as the Internet of Things, cloud computing, big data, and intelligent transportation systems. Furthermore, this paper proposes a multi-layered protection system and strategies for smart city network security, aiming to improve the network security assurance level of smart cities. The research seeks to provide practical protection measures to help smart cities cope with the growing security threats and ensure their sustainable development.

This paper studies underwater optical image target detection and network security protection methods based on deep learning. The YOLOv7-based method is used to solve the color distortion and blur caused by the scattering and absorption of light. By replacing the ELAN structure in the backbone network with the NewDSCLayer structure, the ELAN structure in the detection head module with the GSCLayer structure, and introducing the SimAM attention mechanism, the detection accuracy of overlapping targets and small targets is effectively improved, and the detection speed is also improved. In addition, this paper also designs an adaptive network security protection strategy based on deep reinforcement learning, which can identify multiple network threats through behavior analysis and feature matching, and dynamically adjust defense measures. Experiments have shown that the algorithm proposed in this paper has higher accuracy, faster response speed and higher system stability, and can provide efficient protection for network security.

The new power system has a new operation mode of "the source follows the load, the load follows the network, and the source loads interact". With the continuous excavation of flexible regulation resources, new third-party entities such as virtual power plants or load integrators need to consider implementing differentiated network security protection requirements to ensure their fair access to business. At the same time, with the clarity of the regulation level of the new power system and the continuous participation of various entities in the construction, the company's network security protection boundary will no longer be "horizontal and vertical", but will become more uneven, with more types of interfaces and interfaces. It is necessary to refine the boundary protection measures according to different interaction needs. The new regulatory subject on the demand side of the new power system involves the privacy information of a large number of users. Data flow and sharing, cross access and collaborative analysis among the subjects have security problems such as unauthorized access and privacy leakage. This paper focuses on the scenario based intelligent desensitization and dynamic access control technology for power distribution and distributed new energy data resources, and combs various factors involved in the data access process, On the basis of obtaining the data access authority, the dynamic correlation analysis of the three elements of user role and access authority, sensitive data level, power allocation and distributed new energy business scenario is integrated, and finally the appropriate desensitization method is selected from the desensitization algorithm library, and finally the appropriate desensitization method is selected from the desensitization algorithm library to ensure the security protection capability of the new distribution network under the flexible, open and interactive energy scenario, Effectively respond to new major network security risks.

This paper analyzes Internet sites often present invasion of widespread computer virus, network security has become very prominent, but mainly include infrastructure security, border security, network, network connection security, management of safety in four areas. Good solution to network security, we must start from the four areas. The current firewall technology, vulnerability scanning, intrusion detection, virtual private network technology, encryption and decryption technology, viruses are anti-kill technology to solve a certain level of security technology. As an overall network security protection, a technology is difficult to do alone, must combine a variety of security technologies complement each other. The only way to the need to protect the network put up a barrier, in the normal network access, while security is well ensured accordingly.

To address the complex and variable attack patterns prevalent in the current cybersecurity landscape, as well as the limitations of traditional detection methods concerning sensing range, accuracy and efficiency, an innovative intelligent detection model for cybersecurity was proposed. First, we design a distributed multi-target finite sensing mechanism with complementary fields of view, significantly extending the sensing range by optimizing sensor layout and collaboration strategies. Second, this study constructs a multi-scale attention network model (MSANet), which enhances the feature extraction and expression capabilities of the model without imposing additional computational burdens, thereby enabling more accurate recognition of cyber-attack patterns across different scales. Finally, leveraging the extensive data provided by the distributed perception system and the robust learning capabilities of MSANet, we develop a label-free intelligent detection model for network security. This model effectively addresses the detection challenges arising from feature distribution discrepancies between the target and source network domains, achieving efficient and accurate detection in environments with no labeled or limited labeled data. This advancement provides substantial technical support for network security protection. Experimental results demonstrate that our approach achieves accuracy rates of 98.2%, 96.7% and 99.5%, as well as F1-scores of 97.9%, 95.8% and 97.9%, respectively, in detecting botnet traffic, background traffic and normal traffic within the CTU network traffic dataset. In summary, this study not only enriches the theoretical framework of network security detection but also offers practical solutions for constructing an efficient and intelligent network security protection system, possessing significant theoretical value and promising application prospects.

Network situation value is an important index to measure network security. Establishing an effective network situation prediction model can prevent the occurrence of network security incidents, and plays an important role in network security protection. Through the understanding and analysis of the network security situation, we can see that there are many factors affecting the network security situation, and the relationship between these factors is complex., it is difficult to establish more accurate mathematical expressions to describe the network situation. Therefore, this paper uses the grey neural network as the prediction model, but because the convergence speed of the grey neural network is very fast, the network is easy to fall into local optimum, and the parameters can not be further modified, so the Multi-Swarm Chaotic Particle Optimization (MSCPO)is used to optimize the key parameters of the grey neural network. By establishing the nonlinear mapping relationship between the influencing factors and the network security situation, the network situation can be predicted and protected.

In the global wave of digitalization, the digital preservation of Chinese Ming Dynasty landscape paintings has achieved remarkable results. According to statistics, major museums in China have scanned more than 60% of Ming Dynasty landscape paintings with high precision, and the digital preservation work covers a wide range. However, the accompanying cybersecurity challenges cannot be ignored either. In recent years, cyber attacks on digital platforms of cultural heritage have occurred frequently. Worldwide, the number of such attacks has exceeded 3 million every year, of which attacks on works of art account for as high as 15%. Faced with this grim situation, China has taken a series of measures to strengthen network security protection. By upgrading encryption technology, optimizing network security protection systems, and conducting regular network security training and drills, China has made remarkable progress in ensuring the security of digital works of art. According to the latest data, since the implementation of enhanced protection measures, the number of cyber attacks on the digital platform of landscape painting in Ming Dynasty in China has decreased by 35%, effectively protecting precious cultural heritage from cyber threats.

To safeguard user privacy, critical Internet traffic is often transmitted using encryption. While encryption is crucial for protecting sensitive information, it poses challenges for traffic identification and poses hidden dangers to network security. As a result, the precise classification of encrypted network traffic has become a crucial problem in network security. In light of this, our paper proposes an encrypted traffic identification method based on the C-LSTM model for encrypted traffic recognition by leveraging the power of deep learning. This method can effectively extract spatial and temporal features from encrypted traffic, enabling accurate identification of traffic types. Through rigorous testing and evaluation, our system has achieved an impressive accuracy rate of 96.4% on the widely used ISCXVPN2016 dataset. This achievement demonstrates the effectiveness and reliability of our method in accurately classifying encrypted network traffic. By addressing the challenges posed by encrypted traffic identification, our research contributes to enhancing network security and privacy protection.

This study examined the effects of information technology (IT) on policy decision-making processes, especially in the stages of goal setting and choosing among policy alternatives. It used survey data collected in 1998 and 2005 from the metropolitan areas of Seoul and Busan in Korea. The survey results showed that there has been a positive change in the perception of the effects of IT on policy decision-making processes among government users. These changes could be made possible by strong leadership and e-government initiatives in central and metropolitan governments, not just due to the diffusion of technology and technologically capable staff members in organizations. The empirical results also showed that barriers to information sharing had increased in 2005 because of environmental changes, including requirement of authorization for providing information, complicated data management, and negative attitudes to information sharing. It suggests that city governments need to provide policy remedies for overcoming obstacles in information sharing in the areas of protection of privacy, network security, and official authorization processes for providing individual information. This study may contribute to the school of e-government and IT policy research as it helps decrease the gap between theory and practice.

Under the background of the construction of “three types and two networks”, the introduction of a large number of heterogeneous intelligent terminals, ubiquitous open networks, interactive real-time control services and wide area interconnected power systems have transmitted the network security risks to all aspects of the power system. The security defense capability of power system is not only the superposition of security defense equipment, but also the excellent network security team. The continuous improvement of the level of network security is inseparable from the accumulation of network security attack and defense technology and practical experience, as well as practical tools and equipment with the characteristics of the power industry. In order to meet the increasingly severe security protection challenges, actively implement the security protection requirements of the power information system, ensure the safe and stable operation of the power system, build a network shooting range suited to the attributes of the power industry, and continuously improve the ability of network security protection, consolidate the foundation of digital transformation to ensure the safe and stable operation of power system and reliable power supply.The safe and stable operation of the information system needs to carry out comprehensive and in-depth vulnerability troubleshooting. In view of the lack of power business loophole mining and security event verification shooting range environment, this paper studies the power security shooting range construction technology.

For the new characteristics of power Internet of Things (IoT), the traditional perimeter-based security model could not satisfy the network security requirements of the power IoT. However, zero trust security model was proposed in the past decades to meet new security challenges of networks. In this paper, the technical characteristics of zero trust security architecture are studied and analyzed. The security protection technology of the power IoT based on zero trust security architecture is proposed. Through identity authentication, application agent, data encryption and other security protection technologies, a fine-grained security control of access mechanism is designed. Our propositions provide a solution and technical exploration for future security protection of the power IoT to help power enterprises build more secure network security.

In this paper we show that it is possible to retrofit a security layer on top of PROFINET IO without changing the underlying transmission system or standards. By introducing security modules, end-to-end network security can be achieved and ensure authentication, integrity and confidentiality for real-time communication. The concept of security modules is a flexible framework and countermeasures can be changed, as security threats and exploits are changing over time. A proof-of-concept implementation shows that it is possible to implement security modules on existing products and secure them against, for example, man-in-the-middle attacks.