• Title/Summary/Keyword: Security Intelligence

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Discovery of Market Convergence Opportunity Combining Text Mining and Social Network Analysis: Evidence from Large-Scale Product Databases (B2B 전자상거래 정보를 활용한 시장 융합 기회 발굴 방법론)

  • Kim, Ji-Eun;Hyun, Yoonjin;Choi, Yun-Jeong
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.87-107
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    • 2016
  • Understanding market convergence has became essential for small and mid-size enterprises. Identifying convergence items among heterogeneous markets could lead to product innovation and successful market introduction. Previous researches have two limitations. First, traditional researches focusing on patent databases are suitable for detecting technology convergence, however, they have failed to recognize market demands. Second, most researches concentrate on identifying the relationship between existing products or technology. This study presents a platform to identify the opportunity of market convergence by using product databases from a global B2B marketplace. We also attempt to identify convergence opportunity in different industries by applying Structural Hole theory. This paper shows the mechanisms for market convergence: attributes extraction of products and services using text mining and association analysis among attributes, and network analysis based on structural hole. In order to discover market demand, we analyzed 240,002 e-catalog from January 2013 to July 2016.

Analysis and Forecasting for ICT Convergence Industries (ICT 융합 산업의 현황 및 전망)

  • Jang, Hee S.;Park, Jong T.
    • Journal of Service Research and Studies
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    • v.5 no.2
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    • pp.15-24
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    • 2015
  • The trade balance for the information and communications technology (ICT) industries in 2014 have reached 863 hundred million dollars as the main export products such as smart phone and semi-conductor increase, since the ICT industries have played an important role in economic growth in Korea. Until now, the consistent supporting of government and investment of company have been doing with the growth of ICT industries, as a result, Korea marked as the first in the UN electronic government preparing index, and rank 12 in the network preparing index through the policy of national information and basic plan of inter-industry convergence. However, as the unstable international economic circumstances, ICT industries is faced with the stagnation, and then preemptive development of products and services for ICT convergence industries is needed to continually get definite ICT Korea image. In this paper, the ICT convergence industry is analyzed and forecasted. In specific, the international and domestic market for cloud, 3D convergence, and internet of things is diagnosed. The market for ICT convergence industries is predicted to be 3.6 trillion dollar in the world, and 110 trillion won in domestic. From the analytical results for technology and services development, the preemptive supporting of the technology development and policy for the internet of things and 3D convergence industries is required. In addition to, through the future forecasting by socio-tech matrix method, the policy supporting for the ICT convergence area of healthcare, fintech, artificial intelligence, body platform, and human security is needed.

Personal Information Detection by Using Na$\ddot{i}$ve Bayes Methodology (Na$\ddot{i}$ve Bayes 방법론을 이용한 개인정보 분류)

  • Kim, Nam-Won;Park, Jin-Soo
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.91-107
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    • 2012
  • As the Internet becomes more popular, many people use it to communicate. With the increasing number of personal homepages, blogs, and social network services, people often expose their personal information online. Although the necessity of those services cannot be denied, we should be concerned about the negative aspects such as personal information leakage. Because it is impossible to review all of the past records posted by all of the people, an automatic personal information detection method is strongly required. This study proposes a method to detect or classify online documents that contain personal information by analyzing features that are common to personal information related documents and learning that information based on the Na$\ddot{i}$ve Bayes algorithm. To select the document classification algorithm, the Na$\ddot{i}$ve Bayes classification algorithm was compared with the Vector Space classification algorithm. The result showed that Na$\ddot{i}$ve Bayes reveals more excellent precision, recall, F-measure, and accuracy than Vector Space does. However, the measurement level of the Na$\ddot{i}$ve Bayes classification algorithm is still insufficient to apply to the real world. Lewis, a learning algorithm researcher, states that it is important to improve the quality of category features while applying learning algorithms to some specific domain. He proposes a way to incrementally add features that are dependent on related documents and in a step-wise manner. In another experiment, the algorithm learns the additional dependent features thereby reducing the noise of the features. As a result, the latter experiment shows better performance in terms of measurement than the former experiment does.

The Details and Outlook of Three Data Acts Amendment in South Korea: With a Focus on the Changes of Domestic Financial and Data Industry (데이터 3법 개정안의 내용과 전망: 국내 금융 및 데이터 산업계의 변화를 중심으로)

  • Kim, Eun-Chan;Kim, Eun-Young;Lee, Hyo-Chan;Yoo, Byung-Joon
    • Informatization Policy
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    • v.28 no.3
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    • pp.49-72
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    • 2021
  • This study analyzes the major content, significances, and future outlook of Three Data Acts amendment enacted in August 2020 in South Korea, with the focus on their impact on the financial and data industries. It seems that the revision of the Credit Information Act will enable the specification of a business which had previously only been regulated as the business of credit inquiry, and also enable the domestic data industry to activate the MyData industry, data trading and platforms, and specify data pseudonymization and trading procedures. For the rational and efficient implementation of the amendments to the Three Data Acts, the Personal Information Protection Committee must be as transparent and lawful in its activities as possible, and fairness must be guaranteed. Even in the utilization of personal information, the development or complementation of the related data processing technologies is essential, and clear data processing methods and areas must be regulated. Furthermore, the amendments must be supported with guarantees and the systematization of a fair competitive system in the data market, stricter regulations on penalties for illegal acts related to data, establishment and strengthening of the related security systems, and reinforcement of the system of cooperation for data transfer.

Design of an Integrated University Information Service Model Based on Block Chain (블록체인 기반의 대학 통합 정보서비스 실증 모델 설계)

  • Moon, Sang Guk;Kim, Min Sun;Kim, Hyun Joo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.2
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    • pp.43-50
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    • 2019
  • Block-chain enjoys technical advantages such as "robust security," owing to the structural characteristic that forgery is impossible, decentralization through sharing the ledger between participants, and the hyper-connectivity connecting Internet of Things, robots, and Artificial Intelligence. As a result, public organizations have highly positive attitudes toward the adoption of technology using block-chain, and the design of university information services is no exception. Universities are also considering the application of block-chain technology to foundations that implement various information services within a university. Through case studies of block-chain applications across various industries, this study designs an empirical model of an integrated information service platform that integrates information systems in a university. A basic road map of university information services is constructed based on block-chain technology, from planning to the actual service design stage. Furthermore, an actual empirical model of an integrated information service in a university is designed based on block-chain by applying this framework.

A Study on the Design and Implementation of Multi-Disaster Drone System Using Deep Learning-Based Object Recognition and Optimal Path Planning (딥러닝 기반 객체 인식과 최적 경로 탐색을 통한 멀티 재난 드론 시스템 설계 및 구현에 대한 연구)

  • Kim, Jin-Hyeok;Lee, Tae-Hui;Han, Yamin;Byun, Heejung
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.4
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    • pp.117-122
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    • 2021
  • In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

Trend Forecasting and Analysis of Quantum Computer Technology (양자 컴퓨터 기술 트렌드 예측과 분석)

  • Cha, Eunju;Chang, Byeong-Yun
    • Journal of the Korea Society for Simulation
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    • v.31 no.3
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    • pp.35-44
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    • 2022
  • In this study, we analyze and forecast quantum computer technology trends. Previous research has been mainly focused on application fields centered on technology for quantum computer technology trends analysis. Therefore, this paper analyzes important quantum computer technologies and performs future signal detection and prediction, for a more market driven technical analysis and prediction. As analyzing words used in news articles to identify rapidly changing market changes and public interest. This paper extends conference presentation of Cha & Chang (2022). The research is conducted by collecting domestic news articles from 2019 to 2021. First, we organize the main keywords through text mining. Next, we explore future quantum computer technologies through analysis of Term Frequency - Inverse Document Frequency(TF-IDF), Key Issue Map(KIM), and Key Emergence Map (KEM). Finally, the relationship between future technologies and supply and demand is identified through random forests, decision trees, and correlation analysis. As results of the study, the interest in artificial intelligence was the highest in frequency analysis, keyword diffusion and visibility analysis. In terms of cyber-security, the rate of mention in news articles is getting overwhelmingly higher than that of other technologies. Quantum communication, resistant cryptography, and augmented reality also showed a high rate of increase in interest. These results show that the expectation is high for applying trend technology in the market. The results of this study can be applied to identifying areas of interest in the quantum computer market and establishing a response system related to technology investment.

A Study on the Introductioin of Data Trusts System to Expand the Rights of Privacy Self-Determination (개인정보 자기결정권 확대를 위한 데이터 신탁제도 도입 방안 연구)

  • Jang, Keunjae;Lee, Seungyong
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.29-43
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    • 2022
  • With the advent of the Internet and the development of mobile digital devices such as smartphones and tablet PCs, the communication service paradigm began to shift from existing voice services to data services. Recently, as social network services (SNS) are activated and 4th industrial revolution technologies centered on ICT (Information and Communication Technologies) such as Big Data, Blockchain, Cloud, and 5G/6G are rapidly developed, the amount of shared data type and the amount of data are increasing rapidly. As the transition to a digital society begins actively, the importance of using data information, as well as the economic and social values of personal information are becoming increasingly important. As a result, they are actively discussing policies to revitalize the data information industry around the world and ways to efficiently obtain, analyze, and utilize increasingly diverse and vast data, as well as to protect/guarantee the rights of information subjects (providers) in various fields such as society, culture, economy, and politics.. In this paper, in order to improve the self-determination right of personal information on data produced by information subjects, and further expand the use of safe data and the data economy, a differentiated data trusts system was considered and suggested. In addition, the components and data trusts procedures necessary to efficiently operate the data trusts system in Korea were considered, and the non-profit data trusts system and the for-profit data trusts system were considered as a way to flexibly operate the data trusts system. Furthermore, the legal items necessary for the implementation of the data trusts system were investigated and considered. In this paper, in order to propose a domestic data trusts system, cases related to existing data trusts systems such as the United States, Japan, and Korea were reviewed and analyzed. In addition, in order to prepare legislation necessary for the data trusts system, data-related laws in major countries and domestic legal and policy trends were reviewed to study the rights that conflict or overlap with existing laws, and differences were investigated and considered. The Data trusts system proposed in this paper is a reasonable system that is expected to recognize the asset value of data in the capitalist market economy system, to provide legitimate compensation for data produced by data subjects, and further to contribute greatly to the use of safe data and creation of a new service market.

A Study on the Maritime Law According to the Occurrence of Marine Accidents of MASS(Maritime Autonomous Surface Ship) (자율운항선박의 해양사고 발생에 따른 해상법적 고찰)

  • Lee, Young-Ju
    • Maritime Security
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    • v.6 no.1
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    • pp.37-56
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    • 2023
  • Recently, with the rapid development of ICT(Information and Communication Technology) and AI(Artificial Intelligence) technology industries, the emergence of MASS(Maritime Autonomous Surface Ship), which were thought only in the distant future, is approaching a reality. Along with the development of these amazing technologies, changes in the private law sector, such as liability, compensation for damages, and maritime insurance, as well as in the public law sector, such as maritime safety, marine environment protection, and maintenance of maritime order, have become necessary in the field of maritime law. In particular, with the advent of a new type of ship called MASS that does not have a crew on board, the kind and type of liability, compensation for damages, and insurance contracts in the event of a marine accident will also change. In this paper, the general theory about concept, classification, effectiveness and future of MASS and the general theory about concept and various obligations and responsibilities under the maritime law for discussion of MASS are reviewed. Next, in addition, regarding the problems that may occur in the event of a marine accident from MASS, the status as a ship, the legal relationship of the chartering contract, obligation to exercise due diligence in making the vessel seaworthiness, subject of responsibility, and liability for damages and immunity are reviewed from the perspective of maritime law. In addition, in the degree four of MASS, the necessities of further research to clarify the attributable subjects and standards of responsibility in the event of a marine accident, as well as the necessities of institutional improvement such as technology development, enactment and amendment of law and funding are presented.

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Unsupervised Learning-Based Threat Detection System Using Radio Frequency Signal Characteristic Data (무선 주파수 신호 특성 데이터를 사용한 비지도 학습 기반의 위협 탐지 시스템)

  • Dae-kyeong Park;Woo-jin Lee;Byeong-jin Kim;Jae-yeon Lee
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.147-155
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    • 2024
  • Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.