• Convergence Security Journal
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• v.6 no.2
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• pp.31-42
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• 2006

In this paper, we proposed an integrated infrastructure for optimal information security to resolve these kinds of problems and to implement more powerful protection. The proposed infrastructure presents a security framework, provides a functional mechanism, and implements a scheme for information security based on the design concept of integrated structures. In order to ensure effective malicious traffic blocking, this paper emphasizes that a comprehensive approach through infrastructure improvement and combination of scanning tool is the only measure for preparing against today's environment of virus infiltration. The proposed model is a measure developed at a time when a permanent technological solution to virus is yet to be developed. A performance analysis model is developed and the performance is evaluated through the case studies for the proposed methodology. The effectiveness of the infrastructure for optimal information security needs the continuous diagnostic evaluation and tuning through the users or the organizations.

• Convergence Security Journal
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• v.6 no.4
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• pp.41-47
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• 2006

Spyware is any technology that aids in gathering information about a person or organization with-out their knowledge. Software designed to serve advertising, known as adware, can usually be thought of as spyware as well because it almost invariably includes components for tracking and reporting user information. A piece of spyware and adware affect computers which can rapidly become infected with large numbers of spyware and adware components. Users frequently notice from un-wanted behavior and degradation of system performance, such as significant unwanted CPU activity, disk usage, and network traffic which thereby slows down legitimate uses of these resources. The presence of situation will continue because of rapid expansion of Internet usages. Therefore, security solutions, such as anti-adware and anti-spyware, for recovering these malfunction due to the malicious programs must be developed. However, studies on the malicious programs are still not sufficient. Accordingly, this paper has studied the malicious program techniques, based on the results of analysis of present adware and spyware techniques by employing collected samples, and presents efficient measures for blocking and remedying the malicious programs.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.327-334
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• 2018

When a PC is infected with a malicious code, it communicates with the control and command (C&C) server and, by the attacker's instructions, spreads to the internal network and acquires information. The company focuses on preventing attacks from the outside in advance, but malicious codes aiming at APT attacks are infiltrated into the inside somehow. In order to prevent the spread of the damage, it is necessary to perform internal monitoring to detect a PC that is infected with malicious code and attempts to communicate with the C&C server. In this paper, a destination IP monitoring method is proposed in this paper using Bloom filter to quickly and effectively check whether the destination IP of many packets is in the blacklist.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.99-110
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• 2023

This study proposed a classification of malicious network traffic using the cyber threat framework(Mitre ATT&CK) and machine learning to solve the real-time traffic detection problems faced by current security monitoring systems. We applied a network traffic dataset called UNSW-NB15 to the Mitre ATT&CK framework to transform the label and generate the final dataset through rare class processing. After learning several boosting-based ensemble models using the generated final dataset, we demonstrated how these ensemble models classify network traffic using various performance metrics. Based on the F-1 score, we showed that XGBoost with no rare class processing is the best in the multi-class traffic environment. We recognized that machine learning ensemble models through Mitre ATT&CK label conversion and oversampling processing have differences over existing studies, but have limitations due to (1) the inability to match perfectly when converting between existing datasets and Mitre ATT&CK labels and (2) the presence of excessive sparse classes. Nevertheless, Catboost with B-SMOTE achieved the classification accuracy of 0.9526, which is expected to be able to automatically detect normal/abnormal network traffic.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.3108-3115
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• 1999

Frame relay needs UPC function for the multiplexed logical connections to prevent malicious user traffic from incoming to network, to guarantee the QoS of conformed user traffic, and to protect the normal operation of network system. On the FR/ATM interworking in ATM networks, the UPC may be conducted either by cell-based ATM UPC or frame-based FR UPC. Frames come into and traverse ATm networks by segmentation to ATM cells. Of course, FR QoS should be guaranteed in spite of segmentation and reassembly in ATM networks. In this paper, we compared the QoS of cell-based ATM UPC and frame-based FR UPC in terms of analysis and simulation in case of ingress of excess traffic over negotiated traffic parameters at user-to-network interface. Also we studied frame-based UPC schemes including window-based FR UPC and frame-based VSA which is an ATM UPC algorithm recommended by ITU-T. We described introductions to frame relay including frame structure and FR/ATM interworking, FR traffic parameters and their relationship, comparison of FR QoS between frame-based FR UPC and cell-based ATM UPC, comparison of FR UPC schemes, necessities of egress traffic control, and conclusions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5B
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• pp.491-497
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• 2004

In this Paper, we W a Hovel global traffic control architecture to isolate malicious network attacks and protect network infrastructure in Internet backbone networks. Unlike existing methods based on individual packets or flows, since the proposed detection and control methods are operated on the aggregate traffic level, the computational complexity can k significantly reduced, and they are applicable to develop a global defense architecture against network attack. Experimental results show that the proposed scheme can detect the network attack symptoms very exactly and quickly and protect the network resources as well as the normal traffic flows very efficiently.

• Convergence Security Journal
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• v.10 no.1
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• pp.9-17
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• 2010

Internet network routing system is used to prevent spread and distribution of malicious data traffic. The penetration of malicious code and the function of security blocking are performed on the same course of traffic pathway. The security architecture is the concept to distinguish the architecture from the group handling with the traffic on the structure of network which is performed with the function of penetration and security. The security architecture could be different from the criterion of its realm and function, which requires the development and the application of security mechanism for every architecture. For the establishment of security architecture it is needed to show what criterion of net work should be set up. This study is based on analysis of diagnostic weakness structure in the network security architecture and research the criterion for topology factor, security architecture structure map selection, and blocking location and disinfection net. It is shown to increase the effective rate blocking the virus with the proposed method in this paper rather than the traditional network architecture.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.818-825
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• 2016

Network management and anomaly detection are challenges in high-speed networks due to the high volume of packets that has to be analysed. Flow-based analysis is a scalable method which reduces the high volume of network traffic by dividing it into flows. As sampling methods are extensively used in flow generators such as NetFlow, the impact of sampling on the performance of flow-based analysis needs to be investigated. Monitoring using sampled traffic is a well-studied research area, however, the impact of sampling on flow-based anomaly detection is a poorly researched area. This paper investigates flow sampling methods and shows that these methods have negative impact on flow-based anomaly detection. Therefore, we propose an efficient probabilistic flow sampling method that can preserve flow traffic distribution. The proposed sampling method takes into account two flow features: Destination IP address and octet. The destination IP addresses are sampled based on the number of received bytes. Our method provides efficient sampled traffic which has the required traffic features for both flow-based anomaly detection and monitoring. The proposed sampling method is evaluated using a number of generated flow-based datasets. The results show improvement in preserved malicious flows.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.93-101
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• 2009

This paper proposes the detection method of spreading mails which hacker injects malicious codes to steal the information. And I developed the 'Analysis model' which is decoding traffics when hacker's encoding them to steal the information. I researched 'Methodology of intrusion detection techniques' in the computer network monitoring. As a result of this simulation, I developed more efficient rules to detect the PCs which are infected malicious codes in the hacking mail. By proposing this security policy which can be applicable in the computer network environment including every government or company, I want to be helpful to minimize the damage by hacking mail with malicious codes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1307-1323
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• 2014

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.