• Title/Summary/Keyword: Threat Intelligence

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The Influence of Violence Experience and Emotional Intelligence of Nursing Staff in Long-Term Care Hospitals on the Quality of Nursing Service (요양병원 간호인력의 폭력경험과 감성지능이 간호서비스 질에 미치는 영향)

  • Lee, Seounhee;Oh, Jinjoo
    • The Journal of the Korea Contents Association
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    • v.17 no.8
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    • pp.693-704
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    • 2017
  • The present descriptive study investigated the influence of violence experienced by nursing staff in long-term care hospitals and their emotional intelligence on the quality of nursing service. The study participants included 167 nursing staff from 9 different long-term care hospitals in G and C Provinces. Data collected from questionnaires were analyzed using SPSS 23.0 software. While slight differences were found among the subtypes of violence experience, it was found that verbal violence was the most common form in violence, experienced by the nursing staff, followed by physical threat and physical violence. A hierarchical regression analysis performed to investigate the degree of influence of violence experience and emotional intelligence on the quality of nursing service found that violence experience did not significantly affect the quality of nursing service when the general characteristics were controlled whereas emotional intelligence had a significant influence on the quality of nursing service. The results of this study show that, although it is commonly believed that violence experience is a major factor compromising the quality of nursing service, emotional intelligence, which reflects one's ability to utilize and control one's emotions, may actually have a more significant impact on the quality of nursing service. Emotional intelligence can be improved through education and training; therefore, it is necessary to explore ways to improve emotional intelligence of nursing staff such as development of various programs.

A Study on Developing Low Altitude Multi-layer Air Defense System to Protect Megacities in the Korean Peninsula (한국형 메가시티 저고도 다중방공체계 구축 방안)

  • Sin, Ui-Cheol;Cho, Sang Keun;Park, Sung Jun;Sim, Jun Hak;Koo, Ja Hong;Park, Sang-Hyuk
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.393-398
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    • 2022
  • Megacities of the Repulic of Korea(ROK) will have increased by urbanization and the fourth industrial revolution. Mgacities are absolutely the opportunity factor to make human life enriched. Simultaneously, those are the challenge foctor considering the crucial conventional threat such as massive artillery and multiple rocket launcher from the North Korea. Israel that has faced the geopolitical situation of ROK developed the Multi-layer air defense system to offset the low altitude threat from the neighboring nations. As a result, Israel substantially removed plenty of Hamas' rockes and suicidal drones in 2021. Applying Israel's concept, North Korea's low altitude threat toward the ROK's megacities can effectively be eliminated. Furthermore, this Multi-layer air defense system can be a game-changer that gets rid of the low and high altitude threat from North Korea and neighboring nations with both hyperconnected sensor-C2-shooter and artificial intelligence. Through this approach, the ROK will be able to achieve the prosperity and prowth of nation at the center of Megacities concentrated on PMESII(Politics, Military, Economy, Society, Information, and Infrastructure) factors.

A Preemptive Detection Method for Unknown IoT Botnet Based on Darknet Traffic (다크넷 트래픽 기반의 알려지지 않은 IoT 봇넷 선제탐지 방안)

  • Gunyang Park;Jungsuk Song;Heejun Roh
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.267-280
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    • 2023
  • With development of computing and communications technologies, IoT environments based on high-speed networks have been extending rapidly. Especially, from home to an office or a factory, applications of IoT devices with sensing environment and performing computations are increasing. Unfortunately, IoT devices which have limited hardware resources can be vulnerable to cyber attacks. Hence, there is a concern that an IoT botnet can give rise to information leakage as a national cyber security crisis arising from abuse as a malicious waypoint or propagation through connected networks. In order to response in advance from unknown cyber threats in IoT networks, in this paper, We firstly define four types of We firstly define four types of characteristics by analyzing darknet traffic accessed from an IoT botnet. Using the characteristic, a suspicious IP address is filtered quickly. Secondly, the filtered address is identified by Cyber Threat Intelligence (CTI) or Open Source INTelligence (OSINT) in terms of an unknown suspicious host. The identified IP address is finally fingerprinted to determine whether the IP is a malicious host or not. To verify a validation of the proposed method, we apply to a Darknet on real-world SOC. As a result, about 1,000 hosts who are detected and blocked preemptively by the proposed method are confirmed as real IoT botnets.

Intelligence Report and the Analysis Against the Phishing Attack Which Uses a Social Engineering Technique (사회공학기법을 이용한 피싱 공격 분석 및 대응기술)

  • Lee, Dong-Hwi;Choi, Kyong-Ho;Lee, Dong-Chun;J. Kim, Kui-Nam;Park, Sang-Min
    • Convergence Security Journal
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    • v.6 no.4
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    • pp.171-177
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    • 2006
  • The hacking aspect of recent times is changing, the phishing attack which uses a social engineering technique is becoming the threat which is serious in Information Security. It cheats the user and it acquires a password or financial information of the individual and organization. The phishing attack uses the home page which is fabrication and E-mail and acquires personal information which is sensitive and financial information. This study proposes the establishment of National Fishing Response Center, complement of relation legal system Critical intelligence distribution channel of individual and enterprise.

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Prevention of Terrorism Threat and Role of Security Intelligence in New Terrorism (테러리즘 위협 예방과 경호정보의 역할)

  • Baek, Jong Kap;Kim, Tae-hwan
    • Journal of the Society of Disaster Information
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    • v.1 no.1
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    • pp.43-71
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    • 2005
  • Terrorism is the use of violence, especially murder and bombing, in order to achieve political aim or to force a government to do something. Nowadays, instrument of mass destruction are smaller, cheaper, and more readily available. Cellular phones were used as timers in the attacks in Madrid last March. Hijacking an airplane is relatively inexpensive. Finally, the information revolution provides inexpensive means of communication and organization that allow groups once restricted to local and national police jurisdictions to become global. Al Qaeda is said to have established a network in fifty or more countries. These technological and ideological trends increased both the lethality and the difficulty of managing terrorism. Because of the unprecedented scale of Al Qaeda's attacks, the focus is properly on Islamic extremists. But it would be a mistake to limit our concern solely to Islamic terrorists, for that would ignore the way that technology is putting into the hands of deviant groups and individuals' destructive capabilities that were once limited primarily to governments and armies.

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Multi-Scale Dilation Convolution Feature Fusion (MsDC-FF) Technique for CNN-Based Black Ice Detection

  • Sun-Kyoung KANG
    • Korean Journal of Artificial Intelligence
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    • v.11 no.3
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    • pp.17-22
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    • 2023
  • In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

Proposal of Artificial Intelligence Convergence Curriculum for Upskilling of Financial Manpower : Focusing on Private Bankers and Robo-Advisors

  • KIM, JiWon;WOO, HoSung
    • Fourth Industrial Review
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    • v.2 no.1
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    • pp.19-32
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    • 2022
  • Purpose - As new technologies that have led the 4th industrial revolution spread after the COVID-19 pandemic, the business crisis of existing financial institutions and the threat of employee jobs are growing, especially in the financial sector. The purpose of this study is to propose a human-technology convergence curriculum for creating high value-added in financial institutions and upskilling financial manpower. Research design, data, and methodology - In this study, a curriculum was designed to strengthen job competency for Private Bankers, high-quality employees of a bank dealing with high-net-worth owners. The focus of the design is that learners acquire skills to use robo-advisors as a tool and supplement artificial intelligence ethics. Result - The curriculum is organized into a total of 16 classes, and the main contents are changes in the financial environment and financial consumers, the core technology of robo-advisors and AI ethics, and establishment and evaluation of hyper-personalized asset management strategies using robo-advisors. To achieve the educational goal, two evaluations are performed to derive individual tasks and team project results. Conclusion - Human-centered upskilling convergence education will contribute to improving employee value and expanding corporate high value-added business areas by utilizing new technologies as tools. It is expected that the development and application of convergence curriculum in various fields will continue to be advanced in the future.

A Study on Presidential Security Activities of Military Intelligence Investigation Agency - Since the Korean War, from 1950 to the present - (군(軍) 정보수사기관의 대통령 경호활동 고찰: 1950년 한국전쟁 이후부터 현재까지)

  • Choi, Jong-Young;Jung, Ju-Ho
    • Korean Security Journal
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    • no.53
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    • pp.63-79
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    • 2017
  • Defence Security Command is the only military intelligence and investigation agency which is in charge of safeguarding military information and investigating specific crimes such as subversion and disloyalty in military. While the presidential security provided by Defence Security Command, along with Presidential Security Service(PSS) and the police, forms one of three pillars sustaining presidential security, its works and activities have been rarely known to the public due to the military confidentiality. This study looks into some data specialized into the presidential security among works of Defense Security Command by using various resources such as biographies of key people, media reports, and public materials. It reviews the presidential security works in a historical sense that the works have developed and changed in accordance with the historical changes of Defense Security Command, which was rooted in Counter-Intelligence Corps (Teukmubudae in Korean) in 1948 and leads to the present. The study findings are as follows. First, when the Korean War broke out in 1950 and since then the South Korea was under the threat of the North Korean armed forces and left wing forces, Counter-Intelligence Corps(Bangcheopdudae in Korean) took the lead in presidential security more than the police who was in charge of it. Secondly, even after the Presidential Security Office has founded in 1963, the role of the military on presidential security has been extended by changing its titles from Counter-Intelligence Corps to Army Security corps to Armed Forces Security Command. It has developed their provision of presidential security based on the experience at the president Rhee regime when they could successfully guard the president Rhee and the important government members. Third, since the re-establishment into Defence Security Command in 1990, it has added more security services and strengthened its legal basis. With the excellent expertise, it played a pivotal role in the G20 and other state-level events. After the establishment of the Moon Jaeinin government, its function has been reduced or abolished by the National Defense Reform Act. However, the presidential security field has been strengthening by improving security capabilities through reinforcing the organization. This strengthening of the security capacity is not only effective in coping with the current confrontation situation with the hostile North Korean regime, but also is important and necessary in conducting constant monitoring of the military movement and security-threat factors within military during the national security events.

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VPN-Filter Malware Techniques and Countermeasures in IoT Environment (사물인터넷 환경에서의 VPN-Filter malware 기술과 대응방법)

  • Kim, Seung-Ho;Lee, Keun-Ho
    • Journal of Convergence for Information Technology
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    • v.8 no.6
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    • pp.231-236
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    • 2018
  • Recently, a wide variety of IoT environment is being created due to the rapid development of information and communication technology. And accordingly in a variety of network structures, a countless number of attack techniques and new types of vulnerabilities are producing a social disturbance. In May of 2018, Talos Intelligence, the Cisco threat intelligence team has newly discovered 'VPN-Filter', which constitutes a large-scale IoT-based botnet, is infecting consumer routers in over 54 countries around the world. In this paper, types of IoT-based botnets and the attack techniques utilizing botnet will be examined and the countermeasure technique through EXIF metadata removal method which is the cause of connection method of C & C Server will be proposed by examining the characteristics of attack vulnerabilities and attack scenarios of VPN-Filter.

Cyber Threat Intelligence Traffic Through Black Widow Optimisation by Applying RNN-BiLSTM Recognition Model

  • Kanti Singh Sangher;Archana Singh;Hari Mohan Pandey
    • International Journal of Computer Science & Network Security
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    • v.23 no.11
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    • pp.99-109
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    • 2023
  • The darknet is frequently referred to as the hub of illicit online activity. In order to keep track of real-time applications and activities taking place on Darknet, traffic on that network must be analysed. It is without a doubt important to recognise network traffic tied to an unused Internet address in order to spot and investigate malicious online activity. Any observed network traffic is the result of mis-configuration from faked source addresses and another methods that monitor the unused space address because there are no genuine devices or hosts in an unused address block. Digital systems can now detect and identify darknet activity on their own thanks to recent advances in artificial intelligence. In this paper, offer a generalised method for deep learning-based detection and classification of darknet traffic. Furthermore, analyse a cutting-edge complicated dataset that contains a lot of information about darknet traffic. Next, examine various feature selection strategies to choose a best attribute for detecting and classifying darknet traffic. For the purpose of identifying threats using network properties acquired from darknet traffic, devised a hybrid deep learning (DL) approach that combines Recurrent Neural Network (RNN) and Bidirectional LSTM (BiLSTM). This probing technique can tell malicious traffic from legitimate traffic. The results show that the suggested strategy works better than the existing ways by producing the highest level of accuracy for categorising darknet traffic using the Black widow optimization algorithm as a feature selection approach and RNN-BiLSTM as a recognition model.