• KIPS Transactions on Computer and Communication Systems
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• v.10 no.5
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• pp.145-154
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• 2021

Recently, the introduction of Cloud Managing Security Services System to respond to security threats in cloud computing environments is increasing. Accordingly, it is necessary to analyze the security requirements for the Cloud Managing Security Services System. However, the existing research has a problem that does not reflect the virtual environment of the cloud and the data flow of the Cloud Managing Security Services System in the process of deriving the requirements. To solve this problem, it is necessary to identify the information assets of the Cloud Managing Security Services System in the process of threat modeling analysis, visualize and display detailed components of the cloud virtual environment, and analyze the security threat by reflecting the data flow. Therefore, this paper intends to derive the security requirements of the Cloud Managing Security Services System through threat modeling analysis that is an improved existing research.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.92-98
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• 2008

Network data modeling is a essential research for the evaluation for intrusion detection systems performance, network modeling and methods for analyzing network data. In network data modeling, real data from the network must be analyzed and the modeled data must be efficiently composed to reflect a sufficient amount of the original data. In this parer the useful elements of real network data were quantified from packets captured from a huge network. Futhermore, a statistical analysis method was used to find the most effective element for efficiently classifying the modeled data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4531-4544
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• 2021

Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.155-163
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• 2009

We develop a probability model to evaluate information security investment portfolios. We assume that organizations install portfolios of information security countermeasures to mitigate the damage such as loss of the transaction being processed, damage of hardware and data, etc. A queueing model and Its expected value analysis are used to derive the lost cost of transactions being processed, the replacement cost of hardwares, and the recovery cost of data. The net present value for each portfolio is derived and organizations can select the optimal information security investment portfolio by comparing portfolios.

• Journal of Platform Technology
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• v.8 no.4
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• pp.38-46
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• 2020

This study describes how to build a security control system using an open source big data solution so that private companies can build an overall security control infrastructure. In particular, the infrastructure was built using the Elastic Stack, one of the free open source big data analysis solutions, as a way to shorten the cost and development time when building a security control system. A comparative experiment was conducted. In addition, as a result of comparing and analyzing the functions, convenience, service and technical support of the two solution, it was found that the Elastic Stack has advantages in the security control of Big Data in terms of community and open solution. Using the Elastic Stack, security logs were collected, analyzed, and visualized step by step to create a dashboard, input large logs, and measure the search speed. Through this, we discovered the possibility of the Elastic Stack as a big data analysis solution that could replace Splunk.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.129-132
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• 2003

This paper proposes a performance analysis model of security sowers. Performance analysis of security server reflects both the session and data traffic load. The proposed model is the bases of estimating the maximum response time and minimum queue size of a security server comprising a session association processor whose throughput is 1000 connection/s.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.342-347
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• 2022

On Cloud, the important data of the user that is protected on remote servers can be accessed via internet. Due to rapid shift in technology nowadays, there is a swift increase in the confidential and pivotal data. This comes up with the requirement of data security of the user's data. Data is of different type and each need discrete degree of conservation. The idea of data security data science permits building the computing procedure more applicable and bright as compared to conventional ones in the estate of data security. Our focus with this paper is to enhance the safety of data on the cloud and also to obliterate the problems associated with the data security. In our suggested plan, some basic solutions of security like cryptographic techniques and authentication are allotted in cloud computing world. This paper put your heads together about how machine learning techniques is used in data security in both offensive and defensive ventures, including analysis on cyber-attacks focused at machine learning techniques. The machine learning technique is based on the Supervised, UnSupervised, Semi-Supervised and Reinforcement Learning. Although numerous research has been done on this topic but in reference with the future scope a lot more investigation is required to be carried out in this field to determine how the data can be secured more firmly on cloud in respect with the Machine Learning Techniques and cryptographic methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.961-968
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• 2014

In order to prevent leakage of personal information by insiders a large number of companies install pc security solutions like DRM(Digital Right Management), DLP(Data Loss Prevention), Personal information filtering software steadily. However, despite these investments anomalies personal information occurred. To establish proper security policy before implementing pc security solutions, companies can prevent personal information leakage. Furthermore by analyzing the log from the solutions, companies verify the policies implemented effectively and modify security policies. In this paper, we define the required security solutions installed on PC to prevent disclosure of personal information in a variety of PC security solution, plan to integrate operations of the solutions in the blocking personal information leakage point of view and propose security policies through PC security solution log analysis.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.445-451
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• 2013

Cyber terrorism has lately aimed at major domestic financial institutions and broadcasters. A large number of PCs have been infected, so normal service is difficult. As a result, the monetary damage was reported to be very high. It is important to recognize the importance of big data. But security and privacy efforts for big data is at a relatively low level, therefore the marketing offort is very active. This study concerns the analysis of Big Data industry and Big data security threats that are intelligent and the changes in defense technology. Big data, security countermeasures for the future are also presented.

• Convergence Security Journal
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• v.10 no.3
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• pp.9-14
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• 2010

The network architecture and analysis model for evaluating the information security are presented to distribute the reliable and secure multimedia digital contents. Using the firewall and IDS, the function of the proposed model includes the security range, related data collection/analysis, level evaluation and strategy proposal. To develop efficient automatic analysis tool, the inter-distribution algorithm and network design based on the traffic analysis between web-server and user are needed. Furthermore, the efficient algorithm and design of DRM/PKI also should be presented before the development of the automatic information security model.