• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.44-56
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• 2002

For the risk analysis and risk assessment techniques to be effectively applied to the field of information technology (IT) security, it is necessary that the required activities and specific techniques to be applied and their order of applications are to be determined through a proper risk management model. If the adopted risk management model does not match with the characteristics of host organization, an inefficient management of security would be resulted. In this paper, a risk management model which can be well adapted to Korean domestic IT environments is proposed for an efficient security management of IT. The structure and flow of the existing IT-related risk management models are compared and analysed, and their common and/or strong characteristics are extracted and incorporated in the proposed model in the light of typical threat types observed in Korean IT environments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.7 no.3
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• pp.117-128
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• 1997

When computer systems with mandatory access control mechanism are interconnected each other for enforcing the MHS(Message Handling System) security on the multilevel secure distributed network environment, illegal information flow may occurs due to the unexpected cascade vulnerability problem. In this paper, new MHS security policy and security property functions are proposed for preventing the cascade vulnerability.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.97-106
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• 2008

Quality of Protection(QoP) provides a standard that can evaluate networks offering protection. Also, QoP estimates stability of the system by quantifying intensity of the security. Security should be established based on the circumstance which applied to appropriate level, and this should chose a security policy which fit to propose of network because it is not always proportioned that between stability of security mechanism which is used at network and performance which has to be supported by system. With evolving wireless networks, a variety of security services are defined for providing secure wireless network services. In this paper, we propose a new QoP model which makes up for weak points of existing QoP model to choose an appropriate security policy for wireless network. Proposed new QoP model use objectively organized HVM by Flow-based Abnormal Traffic Detection Algorithm for constructing Utility function and relative weight for constructing Total reward function.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1955-1962
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• 2012

Recently the flow of information security has become a user-centered change. This is mostly breach of security by the normal and abnormal entering harmful files during user internet. Therefore, we would like to design security system that breach of security can be prevented in advance to improve using the reliability of DNS and system control in this paper. In other words, we would like to suggest method can be block randomly to access the site which information security system of user-centric is breached harmful files infected in user computer.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.441-444
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• 2016

Peace on the Korean Peninsula is threatened by physical aggressions and cyber terrors such as nuclear tests, missile launchings, senior government officials' smart phone hackings and DDos attacks to banking systems. Cyber attacks such as vulnerability for the hackings, malware distributions are generally defended by passive defense through the detecting signs of first invasion and attack, data analysis, adding library and updating vaccine programs. In this paper the concept of security program based on Google TensorFlow machine learning ability to perform adding libraries and solving security vulnerabilities by itself is researched and proposed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1021-1030
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• 2021

This paper proposes S-CAFG(Stage-based Cyber Attack Flow Graph), a model for effectively describing training scenarios that simulate modern complex cyber attacks. On top of existing graph and tree models, we add a stage node to model more complex scenarios. In order to evaluate the proposed model, we create a complicated scenario and compare how the previous models and S-CAFG express the scenario. As a result, we confirm that S-CAFG can effectively describe various attack scenarios such as simultaneous attacks, additional attacks, and bypass path selection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.719-731
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• 2012

One of the most important point in the Internet crime investigation is tracing back and pointing out a criminal host. However, criminals can forge a crime record stored in the crime host, or can utilize malicious applications in order not to leave a crime record. In addition, criminals can change the source IP address of a crime host and deny their involvement. In this study, we suggests the Network Forensic Evidence Generation and Verification Scheme (NFEGVS) to rectify the current limitation of Network Forensic technologies. This scheme can prove who and when the crime has occurred. In addition, this prevents leaking of symmetric key for guaranteeing certification and integrity of Forensic Evidence by proposing the Timestamp Secret Key Distribution Scheme, and minimizes performance degradation of router when generating forensic evidence with the Flow-Based Selection Scheme. In this paper, we implement the proposed scheme and evaluate overall performance of the proposed system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.687-697
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• 2023

Botnets, whose attack patterns are becoming more sophisticated and diverse, are recognized as one of the most serious cybersecurity threats today. This paper revisits the experimental results of botnet detection using autoencoder, a semi-supervised deep learning model, for UGR and CTU-13 data sets. To prepare the input vectors of autoencoder, we create data points by grouping the NetFlow records into sliding windows based on source IP address and aggregating them to form features. In particular, we discover a simple power-law; that is the number of data points that have some flow-degree is proportional to the number of NetFlow records aggregated in them. Moreover, we show that our power-law fits the real data very well resulting in correlation coefficients of 97% or higher. We also show that this power-law has an impact on the learning of autoencoder and, as a result, influences the performance of botnet detection. Furthermore, we evaluate the performance of autoencoder using the area under the Receiver Operating Characteristic (ROC) curve.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.149-157
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• 2018

In this paper, we propose an attack detection technology using SDN Controller to study security threats in IoT environment. The research methodology has been developed by applying IoT security threat management technology to the IoT layer and analyzing the research trend of applied security technology. The study results show that the effectiveness of the detection method using the sampling method is studied by adding OpenFlow based SDN Controller to the network switch equipment of the existing IoT network. This method can detect the monitoring and attack of the whole network by interworking with IDS and IPS without affecting the performance of existing IoT devices. By applying such improved security threat countermeasure technology, we expect to be able to relieve anxiety of IoT security threat and increase service reliability.

• Information Systems Review
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• v.19 no.3
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• pp.201-228
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• 2017

Vulnerability information, which can cause serious damage to information assets, has become a valuable commodity, thereby leading to the creation of a vulnerability market. Vulnerability information is traded on the vulnerability market from several hundred dollars to hundreds of thousands of dollars depending on its severity and importance, and the types and scope of the vulnerability markets are varying. Based on previous studies on vulnerability markets and hackers, this study empirically analyzed the effects of the security researcher's vulnerability research motivation on his/her vulnerability market use intention. The results are discussed as follows. First, vulnerability research self-efficacy had a significant effect on flow and on white and black market use intention but not on perceived benefit. Second, flow had a significant effect on perceived benefit and on black market use intention but had no effect on white market use intention. Third, perceived profit had a significant effect on white and black market use intention. Fourth, vulnerability research self-efficacy had a significant effect on perceived benefit through flow. Fifth, flow had a significant effect on white and black market use intention through perceived profit. These findings can be used to predict the behavior of security researchers who have experience in exploiting vulnerabilities.