• Title/Summary/Keyword: Threat Decision

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A Probe Prevention Model for Detection of Denial of Service Attack on TCP Protocol (TCP 프로토콜을 사용하는 서비스거부공격 탐지를 위한 침입시도 방지 모델)

  • Lee, Se-Yul;Kim, Yong-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.4
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    • pp.491-498
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    • 2003
  • The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using FCM(Fuzzy Cognitive Maps) that can detect intrusion by the DoS attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The SPuF(Syn flooding Preventer using Fussy cognitive maps) model captures and analyzes the packet informations to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance comparison, the "KDD′99 Competition Data Set" made by MIT Lincoln Labs was used. The result of simulating the "KDD′99 Competition Data Set" in the SPuF model shows that the probe detection rates were over 97 percentages.

A Study on Factors Influencing Privacy Decision Making on the Internet: Focus on Dual-Calculus Model (온라인 환경에서 프라이버시 의사결정에 영향을 미치는 요인에 관한 연구: 이중계산모델을 중심으로)

  • Kim, Sanghee;Kim, Jongki
    • The Journal of Information Systems
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    • v.25 no.3
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    • pp.197-215
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    • 2016
  • Purpose This study aims to investigate the factors that influence decision making in relation to providing personal information on the internet with respect to the integration of the privacy calculus theory and protection motivation theory based on the dual-calculus model proposed by Li(2012). Design/methodology/approach The privacy calculus theory and protection motivation theory have been applied to explain privacy behavior to a certain degree but few studies have been conducted to explain privacy behavior based on the integration of these two theories. Although Li(2012) proposed the dual-calculus model, he only proposed its framework and did not carry out an empirical study. Therefore, this study proposes a research model that integrates these two theories and examines the relationship between the two theories through an empirical study. Findings According to the results of empirical analysis, it was found that all relations have statistically significant explanatory power except the relation between coping appraisal and privacy risk in the risk calculus process. Thus, the results verify that external threat played a decisive role in increasing the risk level of a consumer's privacy. It can be discussed the ways to enhance the privacy behavior of consumer on the internet through these findings.

Hierarchical Lazy Greedy Algorithm for Weapon Target Assignment (무기할당을 위한 계층적 레이지 그리디 알고리즘)

  • Jeong, Hyesun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.4
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    • pp.381-388
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    • 2020
  • Weapon target assignment problem is an essential technology for automating the operator's rapid decision-making support in a battlefield situation. Weapon target assignment problem is a kind of the optimization problem that can build up an objective function by maximizing the number of threat target destructed or maximizing the survival rate of the protected assets. Weapon target assignment problem is known as the NP-Complete, and various studies have been conducted on it. Among them, a greedy heuristic algorithm which guarantees (1-1/e) approximation has been considered a very practical method in order to enhance the applicability of the real weapon system. In this paper, we formulated the weapon target assignment problem for supporting decision-making at the level of artillery. The lazy strategy based on hierarchical structure is proposed to accelerate the greedy algorithm. By experimental results, we show that our algorithm is more efficient in processing time and support the same level of the objective function value with the basic greedy algorithm.

An Empirical Study on the Shipper′s Decision Making Process of Liner Shipping Services : Primarily on the Information Search (정기선 해운서비스의 구매의사 결정에 관한 연구 - 정보탐색을 중심으로 -)

  • 이정관;신한원
    • Journal of the Korean Institute of Navigation
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    • v.24 no.1
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    • pp.73-84
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    • 2000
  • Shipping industry continues to face dramatic changes in its environment ranging from development in containerization, computerization and telecommunications to the emergence of global marketplace. Perhaps the most significant trend - representing both a threat and opportunity - is the increasingly competitive nature of shipping service market. In order for the shipping companies to cope with those improvements and challenges, they should analyze and clarify customer's DM(decision making) process for the purchase of container shipping service. The major research findings from the study were found as follows; 1) The degree of shipper's involvement in purchasing shipping services was found to be a discriminating variable affecting the information sources consisting of personal and non-personal information sources. 2) The positive relationship was found between the experiences on shipping services and non-personal information sources. 3) It was observed that as people had more experience searching for information, the more in depth their searches became. 4) There existed a positive relationship between knowledges on shipping services and information search. 5) According to the SEM analysis, the shipper's information search on shipping services was also found to have a great influence on the shipper's purchasing behavior. The shipper's search was resulted in positive customer satisfaction.

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Next Generation Convergence Security Framework for Advanced Persistent Threat (지능형 지속 위협에 대한 차세대 융합 보안 프레임워크)

  • Lee, Moongoo;Bae, Chunsock
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.9
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    • pp.92-99
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    • 2013
  • As a recent cyber attack has a characteristic that is intellectual, advanced, and complicated attack against precise purpose and specified object, it becomes extremely hard to recognize or respond when accidents happen. Since a scale of damage is very large, a corresponding system about this situation is urgent in national aspect. Existing data center or integration security framework of computer lab is evaluated to be a behind system when it corresponds to cyber attack. Therefore, this study suggests a better sophisticated next generation convergence security framework in order to prevent from attacks based on advanced persistent threat. Suggested next generation convergence security framework is designed to have preemptive responses possibly against APT attack consisting of five hierarchical steps in domain security layer, domain connection layer, action visibility layer, action control layer and convergence correspondence layer. In domain connection layer suggests security instruction and direction in domain of administration, physical and technical security. Domain security layer have consistency of status information among security domain. A visibility layer of Intellectual attack action consists of data gathering, comparison, decision, lifespan cycle. Action visibility layer is a layer to control visibility action. Lastly, convergence correspond layer suggests a corresponding system of before and after APT attack. An introduction of suggested next generation convergence security framework will execute a better improved security control about continuous, intellectual security threat.

A Study on Priority Decision Method of Required Capability for North West Islands (서북도서에 대한 요구능력 우선순위 결정방법에 관한 연구)

  • Jang, Dong Mo;Lim, Gye Hwan
    • Convergence Security Journal
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    • v.13 no.5
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    • pp.45-56
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    • 2013
  • In order to prepare against the unpredictable provocation of nK on NWI, instead of the threat based force enhancement, sufficient capability based force planning is required in consideration to enemy capability, operations environment, and technological development. This thesis proposes a method on how to prioritize the required capabilities of NWI during the process of identifying capabilities and investing on the decided acquisition assets. Ambiguity in deciding the priority is eliminated and detailed planning is possible through instituting relationship of organization, operation and capability, and by designating weight based on the above relationship. This method identify the various operations and required capabilities, classify the order of priority clearly for NWI, when compare to other method of priority decision. Although capability based force planning requires more assets and faces limitations due to budget, this method will provide and efficient decision making procedure through precise prioritization.

Security tendency analysis techniques through machine learning algorithms applications in big data environments (빅데이터 환경에서 기계학습 알고리즘 응용을 통한 보안 성향 분석 기법)

  • Choi, Do-Hyeon;Park, Jung-Oh
    • Journal of Digital Convergence
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    • v.13 no.9
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    • pp.269-276
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    • 2015
  • Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.

Meltdown Threat Dynamic Detection Mechanism using Decision-Tree based Machine Learning Method (의사결정트리 기반 머신러닝 기법을 적용한 멜트다운 취약점 동적 탐지 메커니즘)

  • Lee, Jae-Kyu;Lee, Hyung-Woo
    • Journal of Convergence for Information Technology
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    • v.8 no.6
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    • pp.209-215
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    • 2018
  • In this paper, we propose a method to detect and block Meltdown malicious code which is increasing rapidly using dynamic sandbox tool. Although some patches are available for the vulnerability of Meltdown attack, patches are not applied intentionally due to the performance degradation of the system. Therefore, we propose a method to overcome the limitation of existing signature detection method by using machine learning method for infrastructures without active patches. First, to understand the principle of meltdown, we analyze operating system driving methods such as virtual memory, memory privilege check, pipelining and guessing execution, and CPU cache. And then, we extracted data by using Linux strace tool for detecting Meltdown malware. Finally, we implemented a decision tree based dynamic detection mechanism to identify the meltdown malicious code efficiently.

Resupply Behavior Modeling in Small-unit Combat Simulation using Decision Trees (소부대 전투 모의를 위한 의사결정트리 기반 재보급 행위 모델링)

  • Seil An;Sang Woo Han
    • Journal of the Korea Society for Simulation
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    • v.32 no.3
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    • pp.9-21
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    • 2023
  • The recent conflict between Russia and Ukraine underscores the significant of military logistics support in modern warfare. Military logistics support is intricate and specialized, and traditionally centered on the mission-level operational analysis and functional models. Nevertheless, there is currently increasing demand for military logistics support even at the engagement level, especially for resupply using unmanned transport assets. In response to the demand, this study proposes a task model of the military logistics support for engagement-level analysis that relies on the logic of ammunition resupply below the battalion level. The model employs a decisions tree to establish the priority of resupply based on variables such as the enemy's level of threat and the remaining ammunition of the supported unit. The model's feasibility is demonstrated through a combat simulation using OneSAF.

Determinants of Satisfaction, Revisit Intention, and Recommendation Intention Using Decision Tree Analysis - Foreign Tourists Visiting Korea during the COVID-19 Pandemic - (의사결정나무분석을 활용한 방문 만족도, 재방문 의사, 타인 권유 의사 결정요인 분석 - 코로나19 상황에서의 한국 방문 외래관광객을 대상으로 -)

  • Won-Sik Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.129-136
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    • 2023
  • The study aims to examine the determinants that affect satisfaction, revisit intention, and recommendation intention with foreign tourists who visited Korea despite the threat of COVID-19. This study employs the survey data collected by the Korea Tourism Organization from 8,135 foreign tourists who visited Korea in 2020. As the survey data contains a mixture of continuous and categorical variables, decision tree analysis can ensure analytical validity for the research. According to the analytical results, the determinants affecting satisfaction are the purpose of the visit and acceptance of self-quarantine during their stay. The factors influencing revisit intention are the purpose of the visit, frequency of the visit, and acceptance of self-quarantine during their stay. The determinants affecting recommendation intention are the purpose of the visit, length of stay, and gender. Based on the results of this analysis, this study not only explains the relationship between these determinants and tourism satisfaction, revisit intention, and recommendation intention, but also suggests implications for revitalizing tourism activities.