• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.59-65
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• 2012

Emergency medical information center performs role of medical direction about disease consult and pre-hospital emergency handling scheme work to people. Emergency medical information system plays a major role to be decreased mortality and disability of emergency patient by providing information of medical institution especially when emergency patient has appeared. But, various attacks as a hacking have been happened in Emergency medical information system recently. In this paper, we proposed security structure which can protect the system securely by detecting attacks from outside effectively. Intrusion detection was performed using rule based detection technique according to protocol for every packet to detect attack and intrusion was reported to control center if intrusion was detected also. Intrusion detection was performed again using decision tree for packet which intrusion detection was not done. We experimented effectiveness using attacks as TCP-SYN, UDP flooding and ICMP flooding for proposed security structure in this paper.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.2
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• pp.3-17
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• 2007

Receiver access control scheme is proposed to protect multicast distribution tree from DoS(Denial-of Service) attack induced by unauthorized use of IGMP(Internet group management protocol), by extending the security-related functionality of IGMP. Based on a specific network and business model adopted for commercial deployment of IP multicast applications, key management scheme is also presented for bootstrapping the proposed access control as well as accounting and billing for CP(Content Provider), NSP(Network Service Provider), and group members.

• Journal of Ecology and Environment
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• v.38 no.1
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• pp.85-93
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• 2015

In 2013, the epidemics of pine wilt disease caused by the pine wood nematodes (Bursaphelenchus xylophilus) resulted in damages to the forests of black pine (Pinus thunbergii Parl.) trees in Jeju Island, Korea. Among the affected trees, an old black pine tree at Cave Temple on Mt. Sanbangsan was included and died due to the prevalence of pine wilt disease. The tree was on Mt. Sanbangsan, which was designated as a National Scenic Place with the Number 77 and was believed to be more than 400 years old in age. By examining the disc of the tree stem obtained from the height of 2 m, we counted the tree rings from 4 different directions and cross-dated the readings by comparing the records of drought simulated from the BROOK Model. Our analysis indicates that the tree seems to have grown since late 1860s. Contrary to the belief of the general public, we can conclude that the age of the tree was estimated to be at maximum 150 years, which means that it was not the same old tree as was shown in the painting of the Tam-Ra-Sun-Ryeok-Do (an old painting book for the Inspection Tour of Jeju Island) published in 1702. Discussion was extended to the life history of the tree in growth and leaning and the measures to protect the tree species from the damages of the pine wilt disease caused by pine wood nematodes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.382-388
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• 2011

This paper proposes a mechanism that guarantees secured performance against DDoS attack to protect data from free-roaming agent. Also, as it makes up QCRT(query chain relationship tree) structure which is an enhanced chain relation of existing chain relations that improves extension, It also finds malicious elements. The proposed mechanism extends chain relationship of agent as well by checking chain relation structure as a structure according to the route of agent. For it complements existing weakness with single-side chain relation extension, it guarantees secure performance against DDoS and truncation attacks from mobile agent.

• The Korean Journal of Ecology
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• v.26 no.1
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• pp.34-38
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• 2003

An analysis of tree ring series of a lace-bark pine (Pinus bungeana Zuccarini) was carried out to find out the exact age of the tree, to describe life history of the tree affected by the change of past environmental factors, and to explain the relationships between the growth fluctuation of the tree and the change of environmental factors of the past. This study explicitly showed that the tree was about 300 years old in 1992 and that the previous estimate of the age to be about 630 years old has no ground to be justified. This was also ascertained by the close correspondence of the tree growth fluctuation to the fluctuation of soil moisture related environmental factors for the last 80 years in Seoul. Although it is clear that the tree suffered from slow growth for about 30 years initiating from the 1910s, it is not sure whether the soil moisture deficits or droughts during the years of 1910-1913 played a major role in causing the decline of the trees afterwards. Discussion was further extended for defining active roles for the Cultural Properties Administration of Korea in management and research to effectively protect the Old and Big Trees under the category of Natural Monument of Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3607-3623
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• 2014

The increasing demand in promoting cloud computing in either business or other areas requires more security of a cloud storage system. Traditional cloud storage systems fail to protect data integrity information (DII), when the interactive messages between the client and the data storage server are sniffed. To protect DII and support public verifiability, we propose a data integrity verification scheme by deploying a designated confirmer signature DCS as a building block. The DCS scheme strikes the balance between public verifiable signatures and zero-knowledge proofs which can address disputes between the cloud storage server and any user, whoever acting as a malicious player during the two-round verification. In addition, our verification scheme remains blockless and stateless, which is important in conducting a secure and efficient cryptosystem. We perform security analysis and performance evaluation on our scheme, and compared with the existing schemes, the results show that our scheme is more secure and efficient.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.32-42
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• 2023

There are serious problems worldwide, such as a pandemic due to an unprecedented infection caused by COVID-19. On previous approaches, they invented medical vaccines and preemptive testing tools for medical engineering. However, it is difficult to access poor medical systems and medical institutions due to disparities between countries and regions. In advanced nations, the damage was even greater due to high medical and examination costs because they did not go to the hospital. Therefore, from a software engineering-based perspective, we propose a learning model for determining coronavirus infection through symptom data-based software prediction models and tools. After a comparative analysis of various models (decision tree, Naive Bayes, KNN, multi-perceptron neural network), we decide to choose an appropriate decision tree model. Due to a lack of data, additional survey data and overseas symptom data are applied and built into the judgment model. To protect from thiswe also adapt human normalization approach with traditional Korean medicin approach. We expect to be possible to determine coronavirus, flu, allergy, and cold without medical examination and diagnosis tools through data collection and analysis by applying decision trees.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.267-267
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• 2019

The purpose of this study is to understand the risk of chemical product, Styrene Monomer(SM), shipped in a vessel. SM is harmful chemical product which can make injury, explosion and/or fire in a vessel. The understand of SM risk is very important to protect seafarer's body and vessel safety. This research can be expected that the understanding of SM risk by a seafarer's to prevent accidents by SM explosion/fire. In this study we used event tree analysis method using chemical reaction cased by explosion. As a result, we founded various chemical reaction and visualization for explosion path.

• 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.

• Journal of KIISE
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• v.44 no.1
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• pp.21-26
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• 2017

In recent years, new technologies such as Internet of Things, Cloud Computing and Big Data are being widely used. And the type and amount of data is dramatically increasing. This makes security an important issue. In terms of leakage of sensitive personal information. In order to protect confidential information, a method called anonymization is used to remove personal identification elements or to substitute the data to some symbols before distributing and sharing the data. However, the existing method performs anonymization by generalizing the level of quasi-identifier hierarchical. It requires a higher level of generalization in case where k-anonymity is not satisfied since records in data table are either added or removed. Loss of information is inevitable from the process, which is one of the factors hindering the utility of data. In this paper, we propose a novel anonymization technique using decision tree based machine learning to improve the utility of data by minimizing the loss of information.