• 기술사
• /
• 제41권2호
• /
• pp.64-67
• /
• 2008

According to grow maritime activities in coastal zone, a threat increase to the marine environment from oil spill. The success or failure of initial effort depends on the adequacy of the plan and the ability of immediate execution. Successful response to oil spills requires critical information in real time topics, including spill data, environmental conditions, ecological factors. Diverse simulation provides tactical decision-makers with the information on the movement of pollutant.

• 한국멀티미디어학회논문지
• /
• 제21권5호
• /
• pp.617-625
• /
• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
• /
• pp.660-663
• /
• 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 Fuzzy Cognitive Maps(FCM) that can detect intrusion by the Denial of Service(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 Sp flooding Preventer using Fuzzy cognitive maps(SPuF) model captures and analyzes the packet information 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. The result of simulating the "KDD ′99 Competition Data Set" in the SPuF model shows that the Probe detection rates were over 97 percentages.

• Journal of Multimedia Information System
• /
• 제5권2호
• /
• pp.99-104
• /
• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• 지능정보연구
• /
• 제12권4호
• /
• pp.127-136
• /
• 2006

본 연구 논문은 육군 전술C4I체계 지원을 위한 전문가시스템 프레임워크를 제시하기 위한 것이다. 한국 육군은 사단급 이상 부대의 전투상황실에서 수작업으로 실시하던 전장정보분석 업무를 지원하기위해 일명 "상황위협평가전문가시스템(STAFS)"개발을 실시한 바 있다. 그러나 기 개발된 STAFS는 종합적인 전투상황실 운영 개념에 부합하는 의사결정체계 구조에 맞추어 개발된 것이 아니고 전술지휘본부 내 임무 중 극히 일부분인 정보융합분석만을 위한 시스템으로 개발되어 실 업무 활용에 많은 제한을 가져 왔다. 따라서 본 논문에서는 이러한 제한점을 개선하여 전투상황실 업무를 종합적으로 지원하는 전문가시스템 프레임워크를 정립하여 지휘관의 의사결정을 지원하기 위한 전문가시스템 개발 구조를 제시하였다.

• Asian Journal for Public Opinion Research
• /
• 제8권3호
• /
• pp.180-196
• /
• 2020

This paper considers Japanese political interviews to integrate conversation and facial expression analysis. The behaviors of political leaders will be disclosed by analyzing questions and responses by using the turn-taking system in conversation analysis. Additionally, audiences who cannot understand verbal expressions alone will understand the psychology of political leaders by analyzing their facial expressions. Integral analyses promote understanding of the types of facial and verbal expressions of politicians and their effect on public opinion. Politicians have unique techniques to convince people. If people do not know these techniques and ways of various expressions, they will become confused, and politics may fall into populism as a result. To avoid this, a complete understanding of verbal and non-verbal behaviors is needed. This paper presents two analyses. The first analysis is a qualitative analysis that deals with Prime Minister Shinzō Abe and shows that differences between words and happy facial expressions occur. That result indicates that Abe expresses disgusted facial expressions when faced with the same question from an interviewer. The second is a quantitative multiple regression analysis where the dependent variables are six facial expressions: happy, sad, angry, surprised, scared, and disgusted. The independent variable is when politicians have a threat to face. Political interviews that directly inform audiences are used as a tool by politicians. Those interviews play an important role in modelling public opinion. The audience watches political interviews, and these mold support to the party. Watching political interviews contributes to the decision to support the political party when they vote in a coming election.

• 한국융합학회논문지
• /
• 제10권9호
• /
• pp.47-53
• /
• 2019

본 논문은 소프트웨어 및 제품의 개발운영 및 개발보안운영에 대한 특성을 검토하고 소프트웨어 코드 관점에서 사용 분석도구를 고찰하였다. 또한 보안 설계규칙을 고려할 때 인적인 요소의 중요성과 이를 강화해야 할 필요성이 강조되었다. 본 논문에서는 개발보안운영을 고려할 때 절차적인 요소의 관점에서 신속하고 정확한 의사결정에 중점을 두고 변화를 관리하는 안전한 프로세스에 대해 분석하였다. 또한 본 논문에서는 개발보안운영 특성과 관련하여 성숙도 모델 분석의 필요성을 논의하였고, 이에 따른 동적인 요소와 정적인 요소의 강도 및 통합 요소에 대한 세부 절차를 통해 분석요소의 의미를 분석하였다. 본 논문에서는 위협모델링 및 컴플라이언스 그리고 통제를 위한 스캔 활동이나 코드 분석과 같은 요소에 대해서도 분석하였다.

• Advances in nano research
• /
• 제10권4호
• /
• pp.397-414
• /
• 2021

The steady growth in population has led to an enhanced water demand and immense pressure on water resources. Pharmaceutical residues (PRs) are unused or non-assimilated medicines found in water supplies that originate from the human and animal consumption of antibiotics, antipyretics, analgesics etc. These have been detected recently in sewage effluents, surface water, ground water and even in drinking water. Due to their toxicity and potential hazard to the environment, humans and aquatic life, PRs are now categorized as the emerging contaminants (ECs). India figures in the top five manufacturers of medicines in the world and every third pill consumed in the world is produced in India. Present day conventional wastewater treatment methods are ineffective and don't eliminate them completely. The use of nanotechnology via advanced oxidation processes (AOP) is one of the most effective methods for the removal of these PRs. Present study is aimed at reviewing the presence of various PRs in water supplies and also to describe the process of AOP to overcome their threat. This study is also very important in view of World Health Organization report confirming more than 30 million cases of COVID-19 worldwide. This will lead to an alleviated use of antibiotics, antipyretics etc. and their subsequent occurrence in water bodies. Need of the hour is to devise a proper treatment strategy and a decision thereof by the policymakers to overcome the possible threat to the environment and health of humans and aquatic life.

• 산업경영시스템학회지
• /
• 제47권2호
• /
• pp.74-83
• /
• 2024

The threat of North Korea's long-range firepower is recognized as a typical asymmetric threat, and South Korea is prioritizing the development of a Korean-style missile defense system to defend against it. To address this, previous research modeled North Korean long-range artillery attacks as a Markov Decision Process (MDP) and used Approximate Dynamic Programming as an algorithm for missile defense, but due to its limitations, there is an intention to apply deep reinforcement learning techniques that incorporate deep learning. In this paper, we aim to develop a missile defense system algorithm by applying a modified DQN with multi-agent-based deep reinforcement learning techniques. Through this, we have researched to ensure an efficient missile defense system can be implemented considering the style of attacks in recent wars, such as how effectively it can respond to enemy missile attacks, and have proven that the results learned through deep reinforcement learning show superior outcomes.

• 정보보호학회논문지
• /
• 제34권3호
• /
• pp.417-430
• /
• 2024

현대 기술의 발전과 인터넷의 보급이 확대되면서 사이버 위협도 증가하고 있다. 이러한 위협에 효과적으로 대응하기 위해 CTI(Cyber Threat Intelligence)의 활용에 대한 중요성이 커지고 있다. 이러한 CTI는 과거의 사이버 위협 데이터에 기반하여 새로운 위협에 대한 정보를 제공하지만, 데이터의 복잡성과 공격 패턴의 변화 등 다양한 요인으로 인해 분석의 어려움을 겪고 있다. 이러한 문제를 해결하기 위해, 본 연구는 다차원적 관계를 포괄적으로 나타낼 수 있는 그래프 데이터의 활용하고자 한다. 구체적으로는 악성코드 데이터를 대상으로 이기종 그래프를 구축하고, metapath2vec의 노드 임베딩 방법을 활용하여 사이버 공격 그룹을 더 효과적으로 식별하고자 한다. 결론적으로 토폴로지 정보를 기존 악성코드 데이터에 추가로 활용하였을 때 탐지성능에 미치는 영향을 분석함으로써, 사이버 보안 분야에 새로운 실질적 적용 가능성을 제시하며, CTI 분석의 한계를 극복하는 데 기여하고자 한다.