Network Security Risk Assessment Research Articles

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

Due to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as firewalls, intrusion detection, and malicious detection technologies offer specific protection based on their unique perspectives. However, as the types and concealment of attacksincrease, these measures struggle to detect them promptly and respond accordingly. In order to meet the social demand for the accuracy and computation speed of the power network security risk evaluation model, the study develops a fusion power network security risk evaluation algorithm by fusing the flash search algorithm with the support vector machine. This algorithm is then used as the foundation for building an improved power network security risk evaluation model based on the fusion algorithm.The study's improved algorithm's accuracy is 96.2%, which is higher than the accuracy of the other comparative algorithms; its error rate is 3.8%, which is lower than the error rate of the other comparative algorithms; and its loss function curve convergence is quicker than that of the other algorithms.The risk evaluation model's accuracy is 97.8%, which is higher than the accuracy of other comparative models; the error rate is 1.9%, which is lower than the error rate of other comparative models; the computing time of the improved power network security risk evaluation model is 4.4 s, which is lower than the computing time of other comparative models; and its expert score is high. These findings are supported by empirical analysis of the improved power network security risk evaluation model proposed in the study. According to the study's findings, the fusion algorithm and the upgraded power network security risk evaluation model outperform other approaches in terms of accuracy and processing speed. This allows the study's maintenance staff to better meet the needs of the community by assisting them in identifying potential security hazards early on and taking the necessary preventative and remedial action to ensure the power system's continued safe operation.

Neural network based single index evaluation for SQL injection attack detection in health care data

In recent years, there are a lot of security risks in the network, and there is the combination intersection between the computer network security problems and security evaluation. The scale of computer network is very large with vast information, so there are many loopholes in the system network. At present, many have established a computer network security evaluation system to monitor the network security vulnerabilities, viruses, and defects in healthcare. However, many places simply analyzed the risk assessment of network security, but there is no assessment of network security situation. For the network security evaluation system, there is no complete evaluation system of network information security. Therefore, a network security evaluation system must be constructed to develop an effective and practical simulation model of computer network security evaluation. Through the simulation model, the effect of network security can be improved. Since the reform and opening up, the simulation of computer network security evaluation in our country is a new subject. It can directly study the network security evaluation, build a network security evaluation model, and study the network security in detail. In the computer network simulation system, it can analyze, study, design, and plan various stages, so as to play an important role.

A fast user actual privilege reasoning framework based on privilege dependency graph reduction

AbstractIt is a key point to find out the actual privileges of network users in network security risk assessment. The Privilege dependency graph (PDG) provides an effective way to reason the actual privileges of network users from their initial privileges. The existing User Actual Privilege reasoning method is time‐consuming and not suitable for large‐scale networks. This paper introduces a fast User Actual Privilege reasoning framework based on PDG reduction. The core idea is to reduce the size of the graph as much as possible before the actual privilege reasoning. Three different nodes merged scenarios are proposed and discussed, as well as the influences of different execution sequences and execution times. Networks of different sizes were simulated to validate the effectiveness and scalability of their method. The experimental results show that the proposed method can decrease the time of User Actual Privilege reasoning by over 25% in large‐scale networks.

Risk assessment of power system network security based on RBF neural network

Risk assessment of power system network security based on RBF neural network

Risk assessment of power system network security based on RBF neural network

Risk assessment of power system network security based on RBF neural network

Analysis of computer network security risk assessment methods

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Computer network security evaluation method based on improved attack graph

ABSTRACT The traditional security detection and defense methods are relatively backward, and there are many problems, such as high false alarm and missed alarm rate, and detection lag, which have been difficult to meet the requirements of computer security defense. In order to strengthen the active defense of computer network security and improve the classification and prediction performance of computer network security events, a computer network security risk assessment model based on mrmr Ig feature selection model and attack graph model is proposed. The mrmr Ig feature selection model is used to classify the characteristics of security events, and the hidden Markov chain model and attack graph model are used to predict the attack intention. The experimental results show that the classification accuracy rate of the model is 99.79%, the false alarm rate and the false alarm rate are 0.11% and 0.18%, respectively. The model can accurately predict attacks in real time, and can provide reference for timely taking targeted computer network security reinforcement and active defense measures.

Network security risk assessment of football matches based on data mining technology

ObjectiveUsing the principles and advanced methods of data mining technology, this paper aims to achieve the analysis and assessment of network security risks under soccer tournaments as a way to help analyze and solve the objective problems such as system vulnerabilities and network viruses that exist in network security today. Faced with various network securities, this paper adopts quantitative risk assessment method. MethodsIn the evaluation of algorithms for constructing network security, the principles and laws of data mining techniques are drawn upon for the analysis and evaluation of network security risks to help analyze the network security risks of soccer tournaments. ResultIt contains 494,020 network connection data, each of which contains 41 connection attributes, including 34 numeric and 7 character attributes. There were 97,277 normal network connections and 396,743 anomalous network connections. In the experiments of the anomaly detection module, although the false positive rate increases compared to all features, the accuracy is basically the same as that of all features with nearly 50% less modeling time and lower false positive rate. So this method is more stable. Therefore, the analysis and assessment of cybersecurity risks are crucial in the present time.

Maintenance of Network Security in Hospital Information Construction Based on the Internet of Things

With the continuous deepening of Chinese medical and health system reform, hospital informatization construction is advancing by leaps and bounds, especially in the context of “Internet of Things + Medical,” hospital informatization construction has made significant progress. However, computer network security management and maintenance work still face many contradictions and problems, and we need to pay attention to them. Based on the analysis of the current situation of computer network security management and maintenance in hospital information construction, this paper focuses on the problems of computer network security management and maintenance and proposes targeted optimization countermeasures. Based on the current problems faced by the medical industry in our country and the state’s support for the medical Internet of Things, this paper studies the application of the Internet of Things in hospital information management at home and abroad. This article uses hospital information network security maintenance evaluation methods and evaluation indicators to conduct an empirical analysis of the information security maintenance level of these 12 hospitals, from the risk assessment of hospital information network security, the establishment of strategies, the level of information security software and hardware equipment, and the information security personnel. Experiments show that 58.33% of the hospitals surveyed have only done part of the work on risk analysis and risk assessment of their own network information security, and 41.67% of the hospitals have not done this work at all. This shows that hospitals should incorporate computer network security management and maintenance into the information construction system, focusing on the outstanding problems and possible risks faced by the arm’s computer network security management and maintenance, and vigorously promote the reform and innovation of computer network security management and maintenance.

Research on modeling method of power system network security risk assessment based on object-oriented Bayesian network

A modeling method of security risk assessment for power system network is presented in this paper. The modeling method is divided into three steps. Firstly, Object-oriented Bayesian network(OOBN) is used for structural modeling to avoid the state explosion caused by the large scale of the network. Secondly, Combined with expert knowledge, an effective parameter modeling method is proposed. Based on the OOBN model, the parallel computing reasoning method of OOBN subnet is studied to reduce the complexity of joint probability calculation and improve the calculation timeliness. Finally, the prototype of power information test system is designed to verify the effectiveness of the model. The results show that the method can be used in the security risk assessment for power system network efficiently.

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.

Research on Key Technologies of Network Security Multidimensional Dynamic Risk Assessment

The emergence of the Internet has had a huge impact on people’s lives and work. In the 21st century, human society has fully entered the Internet age. Through the Internet, people can realize zero-distance, data transmission and information sharing without time and space restrictions. The network has become an important tool for modern people to obtain information, disseminate and share information, and has been applied to almost all fields, from scientific research to astronomy, national defense, medical care, small to home entertainment, production office, web browsing must use the network. However, network security issues have always restricted the application of the network. The network has the characteristics of openness, complexity and speciality. Some lawless elements will steal other people’s information and finance through cyber attacks. The network security problem cannot be ignored. It is important to do a multi-dimensional dynamic risk assessment of network security. This paper will conduct research and analysis on the key technologies of network security multi-dimensional dynamic risk assessment.

Research on Network Security Risk Assessment Method Based on Improved AHP

Aiming at the problem that the data cannot pass the consistency test in the analytic hierarchy process (AHP), an improved AHP is proposed. The implementation scheme of the improved AHP based on D-S evidence theory and gray theory is designed, and matlab is used for simulation experiment. The results show that the improved method can effectively enhance the reliability of network security risk assessment results.

A Network Security Risk Assessment Method Based on a B_NAG Model

Computer networks face a variety of cyberattacks. Most network attacks are contagious and destructive, and these types of attacks can be harmful to society and computer network security. Security evaluation is an effective method to solve network security problems. For accurate assessment of the vulnerabilities of computer networks, this paper proposes a network security risk assessment method based on a Bayesian network attack graph (B_NAG) model. First, a new resource attack graph (RAG) and the algorithm E-Loop, which is applied to eliminate loops in the B_NAG, are proposed. Second, to distinguish the confusing relationships between nodes of the attack graph in the conversion process, a related algorithm is proposed to generate the B_NAG model. Finally, to analyze the reachability of paths in B_NAG, the measuring indexs such as node attack complexity and node state transition are defined, and an iterative algorithm for obtaining the probability of reaching the target node is presented. On this basis, the posterior probability of related nodes can be calculated. A simulation environment is set up to evaluate the effectiveness of the B_NAG model. The experimental results indicate that the B_NAG model is realistic and effective in evaluating vulnerabilities of computer networks and can accurately highlight the degree of vulnerability in a chaotic relationship.

Network Security Risk Assessment of CPS System in Distribution Network Based on Attack Graph

With the development of advanced information and communication technology and intelligent control technology, the modern distribution network has gradually developed into a cyber-physical system of the distribution network, which also brings about the impact of information-side network security threats on the coupling failure of the physical-side power grid. In this context, a method for quantitative assessment of the network security risk of the distribution network CPS system suitable for the principle of power security protection is proposed. First of all, the physical architecture model of a typical distribution network information physical system was built; Secondly, for system network attacks, the attack path data stream related to device vulnerabilities is established, the attack behavior process is modeled based on the attack graph, and the series-parallel model is combined to calculate the success probability of attacking the target circuit breaker; Finally, the article takes the loss of load caused by the action of the attack circuit breaker as the physical consequence to quantify the risk value of the system and complete the network security risk assessment of the system.

Cloud Communication based Ship Communication Network Security Risk Assessment Model

Zhou, H.; Yu, G., Li, L., 2020. Cloud communication based ship communication network security risk assessment model. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 991-995. Coconut Creek (Florida), ISSN 0749-0208.This paper introduces the definition and focus of cloud computing and the development status of cloud computing at home and abroad. The security risk of ship communication network brought by cloud computing is analyzed briefly. Based on the analysis of the relationship between the traditional ship communication information security risk assessment method and the nine elements, a cloud computing-based ship communication network security risk assessment model is proposed. The division of the three models in the cloud computing platform architecture and their interrelationships, starting from the definition and framework, analyzed nine elements (assets, threats, vulnerabilities, security precautions, risks, residual risks, standardization, laws and regulations).Cloud computing ship communication network security risk assessment and their relationship. This model has certain similarities with traditional ship communication information security risk assessment methods, and it also has the particularity of cloud computing. It can well predict the information security of ship communication networks in cloud computing services.

Network security risk assessment model based on fuzzy theory

Network security risk assessment model based on fuzzy theory

I-HMM-Based Multidimensional Network Security Risk Assessment

Cyber-physical systems (CPS) are vulnerable to network attacks because communication relies on the network that links the various components in the CPS. The importance of network security is self-evident. In this study, we conduct a network security risk assessment from the perspectives of the host and the network, and we propose a new framework for a multidimensional network security risk assessment that includes two stages, i.e., risk identification and risk calculation. For the risk identification stage, we propose a multidimensional hierarchical index system for assessing cybersecurity risk; the system's security status is determined in three dimensions, i.e., basic operation, vulnerabilities, and threats, and these dimensions guide the data collection. In the risk calculation stage, we use a hidden Markov model (HMM) to assess the network security risk. We provide a new definition of the quality of alert and optimize the observation sequence of the HMM. The model uses a learning algorithm instead of setting the parameters manually. We introduce the concept of network node association to increase the reliability and accuracy of the risk assessment. The simulation results show that the proposed index system provides quantitative data that reflect the security status of the network. The proposed network security risk assessment method based on the improved HMM (I-HMM) reflects the security risk status in a timely and intuitive manner and detects the degree of risk that different hosts pose to the network.

A review on network security risk assessment and techniques

A network is defined as a group of two or more computers which share resources and communicate among themselves. The most common example of network is internet by which millions of people are connected all over the world. Networks which configure itself on the fly are wireless ad hoc network that is not centralized. It is an infrastructure less network based on IP. Network security is very important and it needs to be maintained because information is getting shared between computers and is vulnerable to attack. We live in a digital world where the need to protect data from hackers is very important. In this paper we are doing a comprehensive survey on network security, wireless ad-hoc network (MANET) and vampire attack.

An improved FAHP-cloud-based security risk assessment model for airborne networks

In connection with problems such as difficulty in the objective and accurate calculation of the index weight in the security risk assessment of an airborne network, as well as a unitary assessment result and poor descriptiveness, a risk assessment method for airborne network security based on an improved fuzzy analytic hierarchy process (FAHP)-cloud model has been proposed. First, the particularity of the airborne network is taken into account to establish an index system for the risk assessment of airborne network security. the traditional FAHP, information entropy is introduced to calculate the comprehensive weight, which is subsequently combined with the cloud model theory to construct an actual integrated cloud model. By calculating the degree of similarity between the actual integrated cloud model and the standard cloud model, the risk levels of airborne network security are determined. The simulation experiments show that this method can reflect the objectivity of the index weight, make the assessment results more visual and reliable, and fully reflect the fuzziness and randomness in the assessment.