• Title/Summary/Keyword: Threat Intelligence

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A Study on the Protective Countermeasures through the Assassination Accident Analysis of Israeli Premier Yitzhak Rabin (라빈수상 위해사건 분석을 통한 경호적 대응방안)

  • Lee, Doo-Suck
    • Korean Security Journal
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    • no.15
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    • pp.221-242
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    • 2008
  • Protection is to maximize the protectee's physical security by minimizing the threats and minimizing the damages caused by the threats. From this point of view, the assassination case of Israel's former Premier Yitzhak Rabin who devoted himself to proceed peace process in Middle East, on November 4, 1995, gives us a lot of lessons on protection. At that time, Israeli society was chaotic with anti-Rabin and anti-government demonstrations which is against Rabin's peace process, and they openly threatened to assassinate Premier Rabin. However, Shin Bet, Israeli Protective Agency, didn't reacted against the assassination threats effectively. Also they have to try to secure friendly public to widen the width of selection in case of crisis and to secure the credibility of the organization. They have to prevent harmful activities in advance by securing wide intelligence networks to collect and analyze various protective intelligences and preparing proper protective countermeasures. Intelligence is a basic element in protection and any protective measures not supported by intelligence activities are not useful and effective. Potential attackers study their target thoroughly and make an elaborate plan before their attack. Advance team is required to conduct security measures on a basis of analysis of vulnerability and threat factors, and close protection team should be prepared for the changing situations with crisis-consciousness. Is security, 100% perfection is not possible. However, Shin Bet failed to analyze and approach to the existing threats. They forgot the fact that security environment reflects social situations. Protection agents should be conscious of the fact that today is different from yesterday. So we have to expect what is not expected when not expected.

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Development of Integrated Security Control Service Model based on Artificial Intelligence Technology (인공지능 기술기반의 통합보안관제 서비스모델 개발방안)

  • Oh, Young-Tack;Jo, In-June
    • The Journal of the Korea Contents Association
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    • v.19 no.1
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    • pp.108-116
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    • 2019
  • In this paper, we propose a method to apply artificial intelligence technology efficiently to integrated security control technology. In other words, by applying machine learning learning to artificial intelligence based on big data collected in integrated security control system, cyber attacks are detected and appropriately responded. As technology develops, many large capacity Is limited to analyzing individual logs. The analysis method should also be applied to the integrated security control more quickly because it needs to correlate the logs of various heterogeneous security devices rather than one log. We have newly proposed an integrated security service model based on artificial intelligence, which analyzes and responds to these behaviors gradually evolves and matures through effective learning methods. We sought a solution to the key problems expected in the proposed model. And we developed a learning method based on normal behavior based learning model to strengthen the response ability against unidentified abnormal behavior threat. In addition, future research directions for security management that can efficiently support analysis and correspondence of security personnel through proposed security service model are suggested.

A Novel Approach to COVID-19 Diagnosis Based on Mel Spectrogram Features and Artificial Intelligence Techniques

  • Alfaidi, Aseel;Alshahrani, Abdullah;Aljohani, Maha
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.195-207
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    • 2022
  • COVID-19 has remained one of the most serious health crises in recent history, resulting in the tragic loss of lives and significant economic impacts on the entire world. The difficulty of controlling COVID-19 poses a threat to the global health sector. Considering that Artificial Intelligence (AI) has contributed to improving research methods and solving problems facing diverse fields of study, AI algorithms have also proven effective in disease detection and early diagnosis. Specifically, acoustic features offer a promising prospect for the early detection of respiratory diseases. Motivated by these observations, this study conceptualized a speech-based diagnostic model to aid in COVID-19 diagnosis. The proposed methodology uses speech signals from confirmed positive and negative cases of COVID-19 to extract features through the pre-trained Visual Geometry Group (VGG-16) model based on Mel spectrogram images. This is used in addition to the K-means algorithm that determines effective features, followed by a Genetic Algorithm-Support Vector Machine (GA-SVM) classifier to classify cases. The experimental findings indicate the proposed methodology's capability to classify COVID-19 and NOT COVID-19 of varying ages and speaking different languages, as demonstrated in the simulations. The proposed methodology depends on deep features, followed by the dimension reduction technique for features to detect COVID-19. As a result, it produces better and more consistent performance than handcrafted features used in previous studies.

Improved Security Monitoring and Control Using Analysis of Cyber Attack in Small Businesses (중소기업 유해트래픽 분석을 통한 보안관제 개선 방안)

  • Hong, Jun Suk;Lim, Young Hwan;Park, Won Hyung;Kook, Kwang Ho
    • The Journal of Society for e-Business Studies
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    • v.19 no.4
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    • pp.195-204
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    • 2014
  • Recent, Secure the small and medium-sized enterprises from advanced and intelligence cyber threat, 24 hours of prevention, detection and analysis is essential. Small and Medium Business monitoring center is operated by government financial support to protect and prevent these threats. Currently it provides security to about 900 small and medium-sized enterprises. This paper studies abnormal and attack packets from small and medium-sized businesses[enterprises] which is monitored by Small and Medium Business monitoring center and provides improvement of security control for small and medium-sized enterprises.

Cyber Threats Prediction model based on Artificial Neural Networks using Quantification of Open Source Intelligence (OSINT) (공개출처정보의 정량화를 이용한 인공신경망 기반 사이버위협 예측 모델)

  • Lee, Jongkwan;Moon, Minam;Shin, Kyuyong;Kang, Sungrok
    • Convergence Security Journal
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    • v.20 no.3
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    • pp.115-123
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    • 2020
  • Cyber Attack have evolved more and more in recent years. One of the best countermeasure to counter this advanced and sophisticated cyber threat is to predict cyber attacks in advance. It requires a lot of information and effort to predict cyber threats. If we use Open Source Intelligence(OSINT), the core of recent information acquisition, we can predict cyber threats more accurately. In order to predict cyber threats using OSINT, it is necessary to establish a Database(DB) for cyber attacks from OSINT and to select factors that can evaluate cyber threats from the established DB. We are based on previous researches that built a cyber attack DB using data mining and analyzed the importance of core factors among accumulated DG factors by AHP technique. In this research, we present a method for quantifying cyber threats and propose a cyber threats prediction model based on artificial neural networks.

Analysis and implications on Ukrainian Military Intelligence Team's Decapitation Operation (우크라이나 군사정보팀의(Military Intelligence Team) 핀셋작전 분석과 시사점)

  • Cho, Sang Keun;Zhytko, Andrii;Park, Sung Jun;Kwon, Bum June;Seo, Kanh ll;Park, Sang-Hyuk
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.6
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    • pp.435-439
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    • 2022
  • ROK has a lot to benchmark from how Ukraine is fighting Russia back with its tactical wins. They have taken a targeted strategy to strike Russia's top generals with high precision. To carry out this strategy, Ukraine is operating a Special Operations Force, which utilizes US/NATO forces, civilian and own resources for maximum impact. Of note, they utilize Starlink for seamless connection from detection, decision-making to strike to maximize operational efficiency. As ROK faces security threat of weapons of mass destruction, Ukraine's military intelligence organization set-up, weapons system and operations can provide some guidance on how to leverage its various SOF as well.

3-Step Security Vulnerability Risk Scoring considering CVE Trends (CVE 동향을 반영한 3-Step 보안 취약점 위험도 스코어링)

  • Jihye, Lim;Jaewoo, Lee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.27 no.1
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    • pp.87-96
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    • 2023
  • As the number of security vulnerabilities increases yearly, security threats continue to occur, and the vulnerability risk is also important. We devise a security threat score calculation reflecting trends to determine the risk of security vulnerabilities. The three stages considered key elements such as attack type, supplier, vulnerability trend, and current attack methods and techniques. First, it reflects the results of checking the relevance of the attack type, supplier, and CVE. Secondly, it considers the characteristics of the topic group and CVE identified through the LDA algorithm by the Jaccard similarity technique. Third, the latest version of the MITER ATT&CK framework attack method, technology trend, and relevance between CVE are considered. We used the data within overseas sites provide reliable security information to review the usability of the proposed final formula CTRS. The scoring formula makes it possible to fast patch and respond to related information by identifying vulnerabilities with high relevance and risk only with some particular phrase.

Research on the application of Machine Learning to threat assessment of combat systems

  • Seung-Joon Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.7
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    • pp.47-55
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    • 2023
  • This paper presents a method for predicting the threat index of combat systems using Gradient Boosting Regressors and Support Vector Regressors among machine learning models. Currently, combat systems are software that emphasizes safety and reliability, so the application of AI technology that is not guaranteed to be reliable is restricted by policy, and as a result, the electrified domestic combat systems are not equipped with AI technology. However, in order to respond to the policy direction of the Ministry of National Defense, which aims to electrify AI, we conducted a study to secure the basic technology required for the application of machine learning in combat systems. After collecting the data required for threat index evaluation, the study determined the prediction accuracy of the trained model by processing and refining the data, selecting the machine learning model, and selecting the optimal hyper-parameters. As a result, the model score for the test data was over 99 points, confirming the applicability of machine learning models to combat systems.

A Study about the Direction and Responsibility of the National Intelligence Agency to the Cyber Security Issues (사이버 안보에 대한 국가정보기구의 책무와 방향성에 대한 고찰)

  • Han, Hee-Won
    • Korean Security Journal
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    • no.39
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    • pp.319-353
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    • 2014
  • Cyber-based technologies are now ubiquitous around the glob and are emerging as an "instrument of power" in societies, and are becoming more available to a country's opponents, who may use it to attack, degrade, and disrupt communications and the flow of information. The globe-spanning range of cyberspace and no national borders will challenge legal systems and complicate a nation's ability to deter threats and respond to contingencies. Through cyberspace, competitive powers will target industry, academia, government, as well as the military in the air, land, maritime, and space domains of our nations. Enemies in cyberspace will include both states and non-states and will range from the unsophisticated amateur to highly trained professional hackers. In much the same way that airpower transformed the battlefield of World War II, cyberspace has fractured the physical barriers that shield a nation from attacks on its commerce and communication. Cyberthreats to the infrastructure and other assets are a growing concern to policymakers. In 2013 Cyberwarfare was, for the first time, considered a larger threat than Al Qaeda or terrorism, by many U.S. intelligence officials. The new United States military strategy makes explicit that a cyberattack is casus belli just as a traditional act of war. The Economist describes cyberspace as "the fifth domain of warfare and writes that China, Russia, Israel and North Korea. Iran are boasting of having the world's second-largest cyber-army. Entities posing a significant threat to the cybersecurity of critical infrastructure assets include cyberterrorists, cyberspies, cyberthieves, cyberwarriors, and cyberhacktivists. These malefactors may access cyber-based technologies in order to deny service, steal or manipulate data, or use a device to launch an attack against itself or another piece of equipment. However because the Internet offers near-total anonymity, it is difficult to discern the identity, the motives, and the location of an intruder. The scope and enormity of the threats are not just focused to private industry but also to the country's heavily networked critical infrastructure. There are many ongoing efforts in government and industry that focus on making computers, the Internet, and related technologies more secure. As the national intelligence institution's effort, cyber counter-intelligence is measures to identify, penetrate, or neutralize foreign operations that use cyber means as the primary tradecraft methodology, as well as foreign intelligence service collection efforts that use traditional methods to gauge cyber capabilities and intentions. However one of the hardest issues in cyber counterintelligence is the problem of "Attribution". Unlike conventional warfare, figuring out who is behind an attack can be very difficult, even though the Defense Secretary Leon Panetta has claimed that the United States has the capability to trace attacks back to their sources and hold the attackers "accountable". Considering all these cyber security problems, this paper examines closely cyber security issues through the lessons from that of U.S experience. For that purpose I review the arising cyber security issues considering changing global security environments in the 21st century and their implications to the reshaping the government system. For that purpose this study mainly deals with and emphasis the cyber security issues as one of the growing national security threats. This article also reviews what our intelligence and security Agencies should do among the transforming cyber space. At any rate, despite of all hot debates about the various legality and human rights issues derived from the cyber space and intelligence service activity, the national security should be secured. Therefore, this paper suggests that one of the most important and immediate step is to understanding the legal ideology of national security and national 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.