• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.179-191
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• 2024

With the advancement of modern technology, cyber-attacks are always rising. Specialized defense systems are needed to protect organizations against these threats. Malicious behavior in the network is discovered using security tools like intrusion detection systems (IDS), firewall, antimalware systems, security information and event management (SIEM). It aids in defending businesses from attacks. Delivering advance threat feeds for precise attack detection in intrusion detection systems is the role of cyber-threat intelligence (CTI) in the study is being presented. In this proposed work CTI feeds are utilized in the detection of assaults accurately in intrusion detection system. The ultimate objective is to identify the attacker behind the attack. Several data sets had been analyzed for attack detection. With the proposed study the ability to identify network attacks has improved by using machine learning algorithms. The proposed model provides 98% accuracy, 97% precision, and 96% recall respectively.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1396-1405
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• 2020

Cyber threats such as forced personal information collection and distribution of malicious codes using malicious URLs continue to occur. In order to cope with such cyber threats, a security technologies that quickly detects malicious URLs and prevents damage are required. In a web environment, malicious URLs have various forms and are created and deleted from time to time, so there is a limit to the response as a method of detecting or filtering by signature matching. Recently, researches on detecting and predicting malicious URLs using machine learning techniques have been actively conducted. Existing studies have proposed various features and machine learning algorithms for predicting malicious URLs, but most of them are only suggesting specialized algorithms by supplementing features and preprocessing, so it is difficult to sufficiently reflect the strengths of various machine learning algorithms. In this paper, a system for predicting malicious URLs using multiple machine learning algorithms was proposed, and an experiment was performed to combine the prediction results of multiple machine learning models to increase the accuracy of predicting malicious URLs. Through experiments, it was proved that the combination of multiple models is useful in improving the prediction performance compared to a single model.

• Convergence Security Journal
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• v.16 no.7
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• pp.139-145
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• 2016

Recently, The attack on the USB and network are increasing in many domestic infrastructure. These attacks are the most independent of insider intention, caused by the Anthropogenic Manipulation. These attacks are Anthropogenic Response Measures for Physical Security. and Representative Technology has CCTV, Access Control System, Sensor Technology. However, Physical Security, it is represented by several Product family according to the Market, has become an obstacle but rather a variety of Physical Security Technology Development and Application. As the Anthropogenic Attacks have occur continually in the network, it need to the proper Physical Response Techniques in this situation. Therefore, In this paper, we will find out about the awareness and demand trends of Physical Security. And The Physical Vulnerable Factors of Network. Thereby this is expected to be utilized as a basis for the domestic Physical Security Technology development and deployment Road-map in a future.

• Journal of the Korea Safety Management & Science
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• v.16 no.1
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• pp.53-68
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• 2014

The purpose of this study is to verify the relationships among innovative behavior, turnover intention, and job security. An additional purpose was to examine partial mediating effects on psychological ownership. The baseline of analyzing those relationships in this study is that the role of psychological ownership will be a mediator between job security and turnover intention as well as innovative behavior in the organization. To accomplish these purposes, a model was built among job security as predictor variable, the psychological ownership as mediating variable and turnover intention, and innovative behavior as criteria variables based on the studies conducted in the various areas. The 248 questionnaires surveyed from the area of DaeGu and Kyungbuk were used in the statistical analyses. The detail statistical techniques are such as descriptive analysis, reliability analysis, factor analysis, correlation analysis, and multi regression analysis. The results of the study show that job security had positively significant effect on turnover intention and innovative behavior. In addition, only the psychological ownership of organization-level thinking have partial mediating effects between job security and innovative behavior also job security and turnover intention. The results may indicate that the psychological ownership of organization-level thinking be a key factor to alleviate the turnover intention of employees and to encourage the innovative behavior during their works for the small-medium size companies showing the unstable job security.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.2
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• pp.81-94
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• 2006

This study, in particular, aims to regulate the core techniques of ubiquitous computing, such as the use of an ad hoc network and the smart-tag technique, and to look more closely into RFID Tag's smart-tag-related security service. The study aims to do so because several important technical factors and structures must be taken into account for RFID Tag to be applied in the ubiquitous-computing-related infrastructure, and the security of the tag is considered one of the core technologies. To realize secure ubiquitous computing in the case of the Passive-tag-Performing RF communication, a less costly security service, the technical items needed to carry this out, a security service to be applied to passive tags, and network management techniques are required. Therefore, the passive-tag-based networks as the authentication level is established based on the secure authentication of each tag and the service that the tag delivers in the passive-tag-based networks and as the same service and authentication levels are applied, and the active-tag-based network system proposed herein is not merely a security service against illegal RFID tags by performing a current-location and service registration process after the secure authentication process of the active RFID tag, but is also a secure protocol for single and group services, is proposed in this study.

• Ocean and Polar Research
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• v.44 no.4
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• pp.355-364
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• 2022

When the 60-ton-class patrol boat '72' of the Korea Coast Guard (KCG) was on duty and she accidentally collided with another patrol boat ('207', 200-ton-class) and sank. A month-long search found a small amount of lost items, but neither the crew nor the ship was found. For the first time in 39 years since the accident, the Korea Institute of Ocean Science and Technology (KIOST) searched the boat 72 using the latest integrated geophysical techniques. A number of sonar images presumed to be of a sunken ship was acquired using a combined system of side scan sonar and marine magnetometer, operated at an altitude of approximately 30 m from the seabed. At the same time, a strong magnetic anomaly (100 nT) was detected in one place, indicating the presence of an iron ship. A video survey using a remotely operated underwater vehicle (ROV) confirmed the presence of a shielding part of a personal firearm at the stern of the sunken vessel. Based on these comprehensive data, the sunken vessel discovered in this exploration was assumed to be '72'. This result is meaningful in terms of future ocean exploration and underwater archaeology, as the integrated system of various geophysical methods is an efficient means of identifying objects present in the water.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.81-88
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• 2015

Recently the Security fields is emerged as a important issue in the world, While a variety of techniques such as a Cloud Computing or a Internet Of Things appeared. In these circumstances, The domestic security fields are divided into the Information Security, the Physical Security and the Convergence Security. and among these security fields, Convergence security is attracted much attention from various industries. the classification systems of a new field Convergence Security has become a very important criteria such about the Statistics calculation, the Analysis of status industry sector and the Road maps. However, In the domestic, The related institutions classified each other differently the Convergence Security Classification. so it is urgently needed a domestic security fields systematic classification due to the problems such as lack of reliability of the accuracy, compatibility of a data. Therefore, this paper will be analyzed to the characteristics of the domestic security classification systems by the cases. and will be proposed the newly improved classification system, to be possible to addition or deletion of an classification entries, and to be easy expanded according to the new technology trends. this proposed to classification system is expected to be utilized as a basis for the construct of a domestic security classification system in a future.

• ETRI Journal
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• v.25 no.6
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• pp.510-516
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• 2003

In this paper, we describe the development of a platform-based SoC of a 32-bit smart card. The smart card uses a 32-bit microprocessor for high performance and two cryptographic processors for high security. It supports both contact and contactless interfaces, which comply with ISO/IEC 7816 and 14496 Type B. It has a Java Card OS to support multiple applications. We modeled smart card readers with a foreign language interface for efficient verification of the smart card SoC. The SoC was implemented using 0.25 ${\mu}m$ technology. To reduce the power consumption of the smart card SoC, we applied power optimization techniques, including clock gating. Experimental results show that the power consumption of the RSA and ECC cryptographic processors can be reduced by 32% and 62%, respectively, without increasing the area.