Machine Learning Models for Heterogenous Network Security Anomaly Detection

The increasing amount and intricacy of network traffic in the modern digital era have worsened the difficulty of identifying abnormal behaviours that may indicate potential security breaches or operational interruptions. Conventional detection approaches face challenges in keeping up with the ever-changing strategies of cyber-attacks, resulting in heightened susceptibility and significant harm to network infrastructures. In order to tackle this urgent issue, this project focused on developing an effective anomaly detection system that utilizes Machine Learning technology. The suggested model utilizes contemporary machine learning algorithms and frameworks to autonomously detect deviations from typical network behaviour. It promptly identifies anomalous activities that may indicate security breaches or performance difficulties. The solution entails a multi-faceted approach encompassing data collection, preprocessing, feature engineering, model training, and evaluation. By utilizing machine learning methods, the model is trained on a wide range of datasets that include both regular and abnormal network traffic patterns. This training ensures that the model can adapt to numerous scenarios. The main priority is to ensure that the system is functional and efficient, with a particular emphasis on reducing false positives to avoid unwanted alerts. Additionally, efforts are directed on improving anomaly detection accuracy so that the model can consistently distinguish between potentially harmful and benign activity. This project aims to greatly strengthen network security by addressing emerging cyber threats and improving their resilience and reliability.

A New Model for Network Security Situation Assessment of the Industrial Internet

To address the problem of network security situation assessment in the Industrial Internet,this paper adopts the evidential reasoning(ER)algorithm and belief rule base(BRB)method to establish an assessment model.First,this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge.Second,the evaluation indicators are fused with expert knowledge and the ER algorithm.According to the fusion results,a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established,and the projection covariance matrix adaptive evolution strategy(P-CMA-ES)is used to optimize the model parameters.This method can not only utilize semiquantitative information effectively but also use more uncertain information and prevent the problem of combinatorial explosion.Moreover,it solves the problem of the uncertainty of expert knowledge and overcomes the problem of low modeling accuracy caused by insufficient data.Finally,a network security situation assessment case of the Industrial Internet is analyzed to verify the effectiveness and superiority of the method.The research results showthat this method has strong applicability to the network security situation assessment of complex Industrial Internet systems.It can accurately reflect the actual network security situation of Industrial Internet systems and provide safe and reliable suggestions for network administrators to take timely countermeasures,thereby improving the risk monitoring and emergency response capabilities of the Industrial Internet.

Research on the Construction of Computer Network Security System in Middle School Campus Network

In order to improve the security of high school campus networks,this paper introduces the goal,system composition,and function of the network security of high school campus networks,and puts forward a series of strategies,including the establishment of network security protection system,data backup and recovery mechanism,and strengthening network security management and training.Through these strategies,the safety and stable operation of the campus network can be ensured,the quality of education can be improved,and school’s development can be promoted.

Network Security Situation Prediction Based on TCAN-BiGRU Optimized by SSA and IQPSO

The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To solve these problems,a combined prediction model based on the temporal convolution attention network(TCAN)and bi-directional gate recurrent unit(BiGRU)network is proposed,which is optimized by singular spectrum analysis(SSA)and improved quantum particle swarmoptimization algorithm(IQPSO).This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data.Furthermore,a prediction model of TCAN-BiGRU is established respectively for each subsequence.TCAN uses the TCN to extract features from the network security situation data and the improved channel attention mechanism(CAM)to extract important feature information from TCN.BiGRU learns the before-after status of situation data to extract more feature information from sequences for prediction.Besides,IQPSO is proposed to optimize the hyperparameters of BiGRU.Finally,the prediction results of the subsequence are superimposed to obtain the final predicted value.On the one hand,IQPSO compares with other optimization algorithms in the experiment,whose performance can find the optimum value of the benchmark function many times,showing that IQPSO performs better.On the other hand,the established prediction model compares with the traditional prediction methods through the simulation experiment,whose coefficient of determination is up to 0.999 on both sets,indicating that the combined prediction model established has higher prediction accuracy.

System Architecture and Key Technologies of Network Security Situation Awareness System YHSAS

Network Security Situation Awareness System YHSAS acquires,understands and displays the security factors which cause changes of network situation,and predicts the future development trend of these security factors.YHSAS is developed for national backbone network,large network operators,large enterprises and other large-scale network.This paper describes its architecture and key technologies:Network Security Oriented Total Factor Information Collection and High-Dimensional Vector Space Analysis,Knowledge Representation and Management of Super Large-Scale Network Security,Multi-Level,Multi-Granularity and Multi-Dimensional Network Security Index Construction Method,Multi-Mode and Multi-Granularity Network Security Situation Prediction Technology,and so on.The performance tests show that YHSAS has high real-time performance and accuracy in security situation analysis and trend prediction.The system meets the demands of analysis and prediction for large-scale network security situation.

Multilevel security model for ad hoc networks

Modern battlefield doctrine is based on mobility, flexibility, and rapid response to changing situations. As is well known, mobile ad hoc network systems are among the best utilities for battlefield activity. Although much research has been done on secure routing, security issues have largely been ignored in applying mobile ad hoc network theory to computer technology. An ad hoc network is usually assumed to be homogeneous, which is an irrational assumption for armies. It is clear that soldiers, commanders, and commanders-in-chief should have different security levels and computation powers as they have access to asymmetric resources. Imitating basic military rank levels in battlefield situations, how multilevel security can be introduced into ad hoc networks is indicated, thereby controlling restricted classified information flows among nodes that have different security levels.

Using the Latin Square Design Model in the Prioritzation of Network Security Threats: A Quantitative Study

Society is becoming increasingly dependent on cyberspace for both business and pleasure. Cyber attackers continue to attack organizational computer networks, as those same computer networks become increasing critical to organizational business process. Strategic planning and managing IT security risks play an important role in the business and government planning process. Deploying defense in depth security measures can ensure that organizations continue to function in times of crisis. This quantitative study explores whether the Latin Square Design (LSD) model can be effectively applied to the prioritization of cybersecurity threats and to the linking of information assurance defense in-depth measures to those threats. The methods used in this study consisted of scanning 10 Cybersecurity Websites such as the Department of Homeland Security US CERT (United States-Computer Emergency Readiness Team [1]) and the SANS Institute (SysAdmin, Audit, Network and Security [2]) using the Likert Scale Model for the Website’s top ten list of cyber threats facing organizations and the network defense in depth measures to fight those threats. A comparison of each cybersecurity threats was then made using LSD to determine whether the Likert scale and the LSD model could be effectively applied to prioritize information assurance measures to protect organizational computing devices. The findings of the research reject the H0 null hypothesis that LSD does not affect the relationship between the ranking of 10 Cybersecurity websites top ten cybersecurity threats dependent variables and the independent variables of defense in depth measures used in protecting organizational devices against cyber-attacks.

Assessing the Risk Situation of Network Security for Active Defense

The risk situation assessment and forecast technique of network security is a basic method of active defense techniques. In order to assess the risk of network security two methods were used to define the index of risk and forecast index in time series, they were analytical hierarchy process （AHP） and support vector regression （SVR）. The module framework applied the methods above was also discussed. Experiment results showed the forecast values were so close to actual values and so it proved the approach is correct.

Key Technologies of Wireless Heterogeneous Network Security

Convergence and collaboration of heterogeneous networks in the next generation public mobile networks will be a subject of universal significance. Convergence of heterogeneous networks, as an effective approach to improve the coverage and capacity of public mobile network, to enable communication services, to provide Internet access and to enable mobile computing from everywhere, has drawn widespread attention for its good prospects in application. Construction of security system for wireless heterogeneous networks and development of new security models, key security techniques and approaches are critical and mandatory in heterogeneous networks development. Key technology of wireless heterogeneous networks security covers security routing protocol, access authentication, intrusion detection system, cooperative communication between nodes, etc.

Application of mobile scanning agent in the network security

To enhance the security of network systems, puts forward a kind of software agent is put forward, which has the induction ability of network frameworks and the ability of behavior independence. It is mobile scanning agent. More attentions is paid to expound how to design and realize mobile scanning agent. Besides, it is also explained the programs of mobile scanning agent system. In the end, it expects mobile scanning agent.

Reform of the Course System of Network Security Theory and Technology for Foreign Students in China

Theory and technology of network security is the core course of information security major,however,it still faces many challenges in the education of foreign graduate students studying in China.This paper analyzes the status quo and existing problems in the course of theory and technology of network security for foreign graduate students studying in China,the most fundamental of which is that the existing teaching materials are difficult to meet the needs of foreign graduate students.In view of the problem,this paper discusses how to improve the existing teaching materials to adapt to the teaching needs for foreign students and puts forward some new ideas and reform measures.

Analysis of Campus Network Security

Campus network provides a critical stage to student service and campus administration,which assumes a paramount part in the strategy of‘Rejuvenating the Country through Science and Education’and‘Revitalizing China through Talented Persons’.However,with the rapid development and continuous expansion of campus network,network security needs to be an essential issue that could not be overlooked in campus network construction.In order to ensure the normal operation of various functions of the campus network,the security risk level of the campus network is supposed to be controlled within a reasonable range at any moment.Through literature research,theory analysis and other methods,this paper systematically combs the research on campus network security at home and abroad,analyzing and researching the campus network security issues from a theoretical perspective.A series of efficient solutions accordingly were also put forward.

ILSM:Incorporated Lightweight Security Model for Improving QOS in WSN

In the network field,Wireless Sensor Networks(WSN)contain prolonged attention due to afresh augmentations.Industries like health care,traffic,defense,and many more systems espoused the WSN.These networks contain tiny sensor nodes containing embedded processors,TinyOS,memory,and power source.Sensor nodes are responsible for forwarding the data packets.To manage all these components,there is a need to select appropriate parameters which control the quality of service of WSN.Multiple sensor nodes are involved in transmitting vital information,and there is a need for secure and efficient routing to reach the quality of service.But due to the high cost of the network,WSN components have limited resources to manage the network.There is a need to design a lightweight solution that ensures the quality of service in WSN.In this given manner,this study provides the quality of services in a wireless sensor network with a security mechanism.An incorporated hybrid lightweight security model is designed in which random waypoint mobility(RWM)model and grey wolf optimization(GWO)is used to enhance service quality and maintain security with efficient routing.MATLAB version 16 andNetwork Stimulator 2.35(NS2.35)are used in this research to evaluate the results.The overall cost factor is reduced at 60%without the optimization technique and 90.90%reduced by using the optimization technique,which is assessed by calculating the signal-to-noise ratio,overall energy nodes,and communication overhead.

On an Interactive Network Security Measur

An interactive network security measure and a description of its function as well as its principle are presented. Based on the existing security loopholes and bugs in operating systems, this measure focuses on the restrictive condition of security and the establishment of configuration files. Under the control and administration of the secure management of configuration files, each system module brings much flexibility, adaptability and high-level security. The security detecting and managing software used in UNIX based on this measure has obtained good results, achieving the goal of automatically detecting and handling inner and outer system-violation and system abuse.

A Research on the Application of Virtual Network Technology in Computer Network Security

In the computer field,network security is a crucial integrant.It is necessary to pay attention on the application of virtual network technology,so as to raise the standard of computer network security to a new level[2].In view of this,this paper will analyze the application of virtual network technology in computer network security and propose some strategies for future reference.

Improved Feistel-based ciphers for wireless sensor network security

Wireless sensor networks (WSNs) are exposed to a variety of attacks. The quality and complexity of attacks are rising day by day. The proposed work aims at showing how the complexity of modern attacks is growing accordingly, leading to a similar rise in methods of resistance. Limitations in computational and battery power in sensor nodes are constraints on the diversity of security mechanisms. We must apply only suitable mechanisms to WSN where our approach was motivated by the application of an improved Feistel scheme. The modified accelerated-cipher design uses data-dependent permutations, and can be used for fast hardware, firmware, software and WSN encryption systems. The approach presented showed that ciphers using this approach are less likely to suffer intrusion of differential cryptanalysis than currently used popular WSN ciphers like DES, Camellia and so on.

Network Security Incidents Frequency Prediction Based on Improved Genetic Algorithm and LSSVM

Since the frequency of network security incidents is nonlinear,traditional prediction methods such as ARMA,Gray systems are difficult to deal with the problem.When the size of sample is small,methods based on artificial neural network may not reach a high degree of preciseness.Least Squares Support Vector Machines (LSSVM) is a kind of machine learning methods based on the statistics learning theory,it can be applied to solve small sample and non-linear problems very well.This paper applied LSSVM to predict the occur frequency of network security incidents.To improve the accuracy,it used an improved genetic algorithm to optimize the parameters of LSSVM.Verified by real data sets,the improved genetic algorithm (IGA) converges faster than the simple genetic algorithm (SGA),and has a higher efficiency in the optimization procedure.Specially,the optimized LSSVM model worked very well on the prediction of frequency of network security incidents.

Study on Network Security Architecture for Power Systems

The wide application of network technology in power systems brings not only convenience and flexibility but also security threats. An architecture of network security for power system was proposed in this study,which protected data and facilities from being attacked by outside users by means of firewall, security monitor and control system. Firewall was basically the first line of defense for the intranet; the security monitoring system was a kind of IDS (Intrusion Detection System), while security control system provided authentication, authorization,data-encrypted transmission and security management. This architecture provides various security services, such as identification, authentication, authorization, data integrity and confidentiality.

Analytical Investigation on Computer Network Security System of Colleges and Universities

With the development of network technology,computer systems of colleges and universities gradually use network management and services,which provides comprehensive and convenient information access and management conditions.How ever,in the network environment,the security of the system faces security threats like virus,malicious software and human at tack,which may make the network data of the computer system damaged and tampered,or even lead to network system paraly sis,breakdown of system concerning management and payment,missing and stealing of confidential documents.Therefore,it is of important application significance to promote the security of computer network systems of colleges and universities.This paper conducts comprehensive analysis on the security system of computer network systems of colleges and universities,elaborates its R&D and application status and puts forward specific schemes of prevention and solutions,which provides suggestions and refer ence for its construction.