The Study on Wireless Mesh Networks Security based on Improved Coding Scheme

In a multi-hop wireless mesh network, wireless links are vulnerable due to severe channel fading, interference and physical damage. In this paper, we will provide a coding scheme to protect from multiple failures in wireless mesh networks to achieve high throughput where the redundancy is considered for the average number of failures. Our coding scheme is designed to protect from the average number of failures to increase the network throughput. When the number of failures is more than the average case, the destination will have to wait for more coded packets in the following time slots.

The Study on Wireless Mesh Networks Security based on Improved Coding Scheme

In a multi-hop wireless mesh network, wireless links are vulnerable due to severe channel fading, interference and physical damage. In this paper, we will provide a coding scheme to protect fi＇om multiple failures in wireless mesh networks to achieve high throughput where the redundancy is considered for the average number of failures. Our coding scheme is designed to protect fi＇om the average number of failures to increase the network throughput. When the number of failures is more than the average case, the destination will have to walt for more coded packets in the following time slots.

A Security Trade-Off Scheme of Anomaly Detection System in IoT to Defend against Data-Tampering Attacks

Internet of Things(IoT)is vulnerable to data-tampering(DT)attacks.Due to resource limitations,many anomaly detection systems(ADSs)for IoT have high false positive rates when detecting DT attacks.This leads to the misreporting of normal data,which will impact the normal operation of IoT.To mitigate the impact caused by the high false positive rate of ADS,this paper proposes an ADS management scheme for clustered IoT.First,we model the data transmission and anomaly detection in clustered IoT.Then,the operation strategy of the clustered IoT is formulated as the running probabilities of all ADSs deployed on every IoT device.In the presence of a high false positive rate in ADSs,to deal with the trade-off between the security and availability of data,we develop a linear programming model referred to as a security trade-off(ST)model.Next,we develop an analysis framework for the ST model,and solve the ST model on an IoT simulation platform.Last,we reveal the effect of some factors on the maximum combined detection rate through theoretical analysis.Simulations show that the ADS management scheme can mitigate the data unavailability loss caused by the high false positive rates in ADS.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

Quality of Service and Security on Cisco Network Devices, Coupled with the Development of a Mobile Application Prototype Software for Server Room Temperature Monitoring

In an era where digital technology is paramount, higher education institutions like the University of Zambia (UNZA) are employing advanced computer networks to enhance their operational capacity and offer cutting-edge services to their academic fraternity. Spanning across the Great East Road campus, UNZA has established one of the most extensive computer networks in Zambia, serving a burgeoning community of over 20,000 active users through a Metropolitan Area Network (MAN). However, as the digital landscape continues to evolve, it is besieged with burgeoning challenges that threaten the very fabric of network integrity—cyber security threats and the imperatives of maintaining high Quality of Service (QoS). In an effort to mitigate these threats and ensure network efficiency, the development of a mobile application to monitor temperatures in the server room was imperative. According to L. Wei, X. Zeng, and T. Shen, the use of wireless sensory networks to monitor the temperature of train switchgear contact points represents a cost-effective solution. The system is based on wireless communication technology and is detailed in their paper, “A wireless solution for train switchgear contact temperature monitoring and alarming system based on wireless communication technology”, published in the International Journal of Communications, Network and System Sciences, vol. 8, no. 4, pp. 79-87, 2015 [1]. Therefore, in this study, a mobile application technology was explored for monitoring of temperatures in the server room in order to aid Cisco device performance. Additionally, this paper also explores the hardening of Cisco device security and QoS which are the cornerstones of this study.

Research on College Network Information Security Protection in the Digital Economy Era

In the era of the digital economy,the informatization degree of various industries is getting deeper and deeper,and network information security has also come into people’s eyes.Colleges and universities are in the position of training applied talents,because of the needs of teaching and education,as well as the requirements of teaching reform,the information construction of colleges and universities has been gradually improved,but the problem of network information security is also worth causing people to ponder.The low security of the network environment will cause college network information security leaks,and even hackers will attack the official website of the university and leak the personal information of teachers and students.To solve such problems,this paper studies the protection of college network information security against the background of the digital economy era.This paper first analyzes the significance of network information security protection,then points out the current and moral problems,and finally puts forward specific countermeasures,hoping to create a safe learning environment for teachers and students for reference.

Security Risk Prevention and Control Deployment for 5G Private Industrial Networks

In this paper,we investigate and analyze the network security risks faced by 5G private industrial networks.Based on current network security architecture and 3GPP requirements and considering the actual application of 5G private industrial networks,a comparative analysis is used to plan and design a private network security construction scheme.The network security construction model,network organization,and key processes of 5G private industrial networks at the current stage are investigated.In addition,the key direction for the next stage of construction is discussed.

AN IMMUNITY-BASED SECURITY ARCHITECTURE FOR MOBILE AD HOC NETWORKS

This paper focuses on investigating immunological principles in designing a multi-agent security architecture for intrusion detection and response in mobile ad hoc networks. In this approach, the immunity-based agents monitor the situation in the network. These agents can take appropriate actions according to the underlying security policies. Specifically, their activities are coordinated in a hierarchical fashion while sensing, communicating, decision and generating responses. Such an agent can learn and adapt to its environment dynamically and can detect both known and unknown intrusions. The proposed intrusion detection architecture is designed to be flexible, extendible, and adaptable that can perform real-time monitoring. This paper provides the conceptual view and a general framework of the proposed system. In the end, the architecture is illustrated by an example to show it can prevent the attack efficiently.

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.

Security Service Technology for Mobile Networks

As mobile networks become high speed and attain an all-IP structure, more services are possible. This brings about many new security requirements that traditional security programs cannot handle. This paper analyzes security threats and the needs of 3G/4G mobile networks, and then proposes a novel protection scheme for them based on their whole structure. In this scheme, a trusted computing environment is constructed on the mobile terminal side by combining software validity verification with access control. At the security management center, security services such as validity verification and integrity check are provided to mobile terminals. In this way, terminals and the network as a whole are secured to a much greater extent. This paper also highlights problems to be addressed in future research and development.

Improving the Cybersecurity Framework for Future Consumer Networks

The framework Information Technology professionals and Network Organizations use is often seen as open and dynamic. This can create many different pathways for cybercriminals to launch an attack on an enterprise network to cause panic, this situation could be prevented. Using the proposed framework, network administrators and networked organizations can improve their cybersecurity framework for future consumer networks. Implementing a network security plan that is up to date and outlines responsibilities of team members, creating a government subsidy to implement and increase safeguards on US based networks, and the analyzing of past cyber-attacks metadata to further understand the attacks that are causing problems for consumer networks can improve the cybersecurity framework for consumer networks and increase potential security on US based networks. Research found that the implementation of security plans, creating a government subsidy, and analyzing past metadata all show signs of improving the framework of cybersecurity in consumer based networks.

Reducing Threats by Using Bayesian Networks to Prioritize and Combine Defense in Depth Security Measures

Studied in this article is whether the Bayesian Network Model (BNM) can be effectively applied to the prioritization of defense in-depth security tools and procedures and to the combining of those measures to reduce cyber threats. The methods used in this study consisted of scanning 24 peer reviewed Cybersecurity Articles from prominent Cybersecurity Journals using the Likert Scale Model for the article’s list of defense in depth measures (tools and procedures) and the threats that those measures were designed to reduce. The defense in depth tools and procedures are then compared to see whether the Likert scale and the Bayesian Network Model could be effectively applied to prioritize and combine the measures to reduce cyber threats attacks against organizational and private computing systems. The findings of the research reject the H0 null hypothesis that BNM does not affect the relationship between the prioritization and combining of 24 Cybersecurity Article’s defense in depth tools and procedures (independent variables) and cyber threats (dependent variables).

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.

Enhancement of UAV Data Security and Privacy via Ethereum Blockchain Technology

Unmanned aerial vehicles(UAVs),or drones,have revolutionized a wide range of industries,including monitoring,agriculture,surveillance,and supply chain.However,their widespread use also poses significant challenges,such as public safety,privacy,and cybersecurity.Cyberattacks,targetingUAVs have become more frequent,which highlights the need for robust security solutions.Blockchain technology,the foundation of cryptocurrencies has the potential to address these challenges.This study suggests a platform that utilizes blockchain technology tomanage drone operations securely and confidentially.By incorporating blockchain technology,the proposed method aims to increase the security and privacy of drone data.The suggested platform stores information on a public blockchain located on Ethereum and leverages the Ganache platform to ensure secure and private blockchain transactions.TheMetaMask wallet for Ethbalance is necessary for BCT transactions.The present research finding shows that the proposed approach’s efficiency and security features are superior to existing methods.This study contributes to the development of a secure and efficient system for managing drone operations that could have significant applications in various industries.The proposed platform’s security measures could mitigate privacy concerns,minimize cyber security risk,and enhance public safety,ultimately promoting the widespread adoption of UAVs.The results of the study demonstrate that the blockchain can ensure the fulfillment of core security needs such as authentication,privacy preservation,confidentiality,integrity,and access control.

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.

Wireless Sensor Security Issues on Data Link Layer:A Survey

A computer network can be defined as many computing devices connected via a communication medium like the internet.Computer network development has proposed how humans and devices communicate today.These networks have improved,facilitated,and made conventional forms of communication easier.However,it has also led to uptick in-network threats and assaults.In 2022,the global market for information technology is expected to reach$170.4 billion.However,in contrast,95%of cyber security threats globally are caused by human action.These networks may be utilized in several control systems,such as home-automation,chemical and physical assault detection,intrusion detection,and environmental monitoring.The proposed literature review presents a wide range of information on Wireless Social Networks(WSNs)and Internet of Things(IoT)frameworks.The aim is first to be aware of the existing issues(issues with traditional methods)and network attacks on WSN and IoT systems and how to defend them.The second is to review the novel work in the domain and find its limitations.The goal is to identify the area’s primary gray field or current research divide to enable others to address the range.Finally,we concluded that configuration.Message Rapid Spanning Tree Protocol(RSTP)messages have higher efficiency in network performance degradation than alternative Bridge Data Unit Protocol(BPDU)forms.The research divides our future research into solutions and newly developed techniques that can assist in completing the lacking component.In this research,we have selected articles from 2015 to 2021 to provide users with a comprehensive literature overview.

Toward Secure Software-Defined Networks Using Machine Learning: A Review, Research Challenges, and Future Directions

Over the past few years,rapid advancements in the internet and communication technologies have led to increasingly intricate and diverse networking systems.As a result,greater intelligence is necessary to effectively manage,optimize,and maintain these systems.Due to their distributed nature,machine learning models are challenging to deploy in traditional networks.However,Software-Defined Networking(SDN)presents an opportunity to integrate intelligence into networks by offering a programmable architecture that separates data and control planes.SDN provides a centralized network view and allows for dynamic updates of flow rules and softwarebased traffic analysis.While the programmable nature of SDN makes it easier to deploy machine learning techniques,the centralized control logic also makes it vulnerable to cyberattacks.To address these issues,recent research has focused on developing powerful machine-learning methods for detecting and mitigating attacks in SDN environments.This paper highlighted the countermeasures for cyberattacks on SDN and how current machine learningbased solutions can overcome these emerging issues.We also discuss the pros and cons of using machine learning algorithms for detecting and mitigating these attacks.Finally,we highlighted research issues,gaps,and challenges in developing machine learning-based solutions to secure the SDN controller,to help the research and network community to develop more robust and reliable solutions.

Empirical Analysis of Neural Networks-Based Models for Phishing Website Classification Using Diverse Datasets

Phishing attacks pose a significant security threat by masquerading as trustworthy entities to steal sensitive information,a problem that persists despite user awareness.This study addresses the pressing issue of phishing attacks on websites and assesses the performance of three prominent Machine Learning(ML)models—Artificial Neural Networks(ANN),Convolutional Neural Networks(CNN),and Long Short-Term Memory(LSTM)—utilizing authentic datasets sourced from Kaggle and Mendeley repositories.Extensive experimentation and analysis reveal that the CNN model achieves a better accuracy of 98%.On the other hand,LSTM shows the lowest accuracy of 96%.These findings underscore the potential of ML techniques in enhancing phishing detection systems and bolstering cybersecurity measures against evolving phishing tactics,offering a promising avenue for safeguarding sensitive information and online security.

Design and Implementation of an Open Network Security Management Platform

In order to manage all kinds of network security devices and software systems efficiently, and make them collaborate with each other, the model for an open network security management platform is presented. The feasibility and key implementing technology of the model are expatiated. A prototype system is implemented to validate it.

Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world.However,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork data.We present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service assaults.We compile a broad dataset of labeled VPN traffic flows from various apps and usage patterns.Next,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous actions.To effectively process and categorize encrypted packets,the neural network model has input,hidden,and output layers.We use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral properties.We also use cutting-edge optimizationmethods to optimize network characteristics and performance.The suggested ANN-based categorization method is extensively tested and analyzed.Results show the model effectively classifies VPN traffic types.We also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%accuracy.This study improves VPN security and protects against new cyberthreats.Classifying VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security problems.This study advances network security and lays the groundwork for ANN-based cybersecurity solutions.