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A Study on the Data-Based Organizational Capabilities by Convergence Capabilities Level of Public Data (공공데이터 융합역량 수준에 따른 데이터 기반 조직 역량의 연구)

  • Jung, Byoungho;Joo, Hyungkun
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.18 no.4
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    • pp.97-110
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    • 2022
  • The purpose of this study is to analyze the level of public data convergence capabilities of administrative organizations and to explore important variables in data-based organizational capabilities. The theoretical background was summarized on public data and use activation, joint use, convergence, administrative organization, and convergence constraints. These contents were explained Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. The research model was set as the data-based organizational capabilities effect by a data-based administrative capability, public data operation capabilities, and public data operation constraints. It was also set whether there is a capabilities difference data-based on an organizational operation by the level of data convergence capabilities. This study analysis was conducted with hierarchical cluster analysis and multiple regression analysis. As the research result, First, hierarchical cluster analysis was classified into three groups. It was classified into a group that uses only public data and structured data, a group that uses public data on both structured and unstructured data, and a group that uses both public and private data. Second, the critical variables of data-based organizational operation capabilities were found in the data-based administrative planning and administrative technology, the supervisory organizations and technical systems by public data convergence, and the data sharing and market transaction constraints. Finally, the essential independent variables on data-based organizational competencies differ by group. This study contributed. As a theoretical implication, this research is updated on management information systems by explaining the Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. As a practical implication, the activity reinforcement of public data should be promoting the establishment of data standardization and search convenience and elimination of the lukewarm attitudes and Selfishness behavior for data sharing.

1.5-factor Authentication Method using Secure Keypads and Biometric Authentication in the Fintech (핀테크 환경에서 보안 키패드와 생체인증을 이용한 1.5-factor 인증 기법)

  • Mun, Hyung-Jin
    • Journal of Industrial Convergence
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    • v.20 no.11
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    • pp.191-196
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    • 2022
  • In the fintech field, financial transactions with smart phones are actively conducted. User authentication technology is essential for safe financial transactions. PIN authentication through the existing security keypads is convenient to input but has weaknesses in security and others. The biometric authentication technique is secure, but there is a possibility of false positive and false negative authentication. To compensate for this, two-factor authentication is used. In this paper, we propose the 1.5-factor authentication that can increase convenience and security through PIN input with biometric authentication. It provides the stability of fingerprint authentication and convenience of two or three PIN inputs, and this makes safe financial transaction possible. Since biometric authentication is performed at the same time when entering PIN, while security is required by applying fingerprint authentication to the area touched while entering PIN. The User authentication is performed while ensuring convenience to input through additional PIN input in situations where high safety is required, and Safe financial transactions are possible.

Development and Application of Private-focused Digital Public Service Evaluation Framework: Focused on AHP Analysis (민간 중심 디지털 공공 서비스 적합성 평가 프레임워크 개발 및 시범 적용 연구: AHP를 중심으로)

  • Sangjun Lee;DaeChul Lee
    • Journal of Information Technology Services
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    • v.22 no.2
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    • pp.71-92
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    • 2023
  • Globally, under the leadership of advanced ICT countries, the private sector is promoting various policies to promote the digital transformation of public services. Looking at the research trend, design of public service indicators, development of evaluation system, and empirical research are being carried out steadily, but there are insufficient research cases on models in which the private sector participates in the planning, development, and operation of public services. In this study, Private-centric digital public service suitability evaluation indicators were discovered through interviews with experts in various fields, and weights for each indicator were analyzed through AHP evaluation. In addition, by applying the analysis results to 18 digital public services on a trial basis, the importance and priority of evaluation indicators for each service were derived, and at the same time, the evaluation framework was designed and applied to diagnose implications. As a result of the study, 'social utility', 'corporate acceptability', and 'public acceptability' were selected as the top three indicators of suitability evaluation. At this time, it was analyzed that the weight of the 'company acceptability' index, which includes sub-indices such as 'service profitability', 'service scalability', and 'private initiative possibility', was the highest among the three top indicators. As a result of the demonstration for public services, "IoT facility unmanned remote monitoring service", "blockchain real estate transaction service", and "digital twin disaster prediction service" were evaluated as the most suitable public services for the transition to the private sector.

Ethereum Phishing Scam Detection based on Graph Embedding and Semi-Supervised Learning (그래프 임베딩 및 준지도 기반의 이더리움 피싱 스캠 탐지)

  • Yoo-Young Cheong;Gyoung-Tae Kim;Dong-Hyuk Im
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.5
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    • pp.165-170
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    • 2023
  • With the recent rise of blockchain technology, cryptocurrency platforms using it are increasing, and currency transactions are being actively conducted. However, crimes that abuse the characteristics of cryptocurrency are also increasing, which is a problem. In particular, phishing scams account for more than a majority of Ethereum cybercrime and are considered a major security threat. Therefore, effective phishing scams detection methods are urgently needed. However, it is difficult to provide sufficient data for supervised learning due to the problem of data imbalance caused by the lack of phishing addresses labeled in the Ethereum participating account address. To address this, this paper proposes a phishing scams detection method that uses both Trans2vec, an effective graph embedding techique considering Ethereum transaction networks, and semi-supervised learning model Tri-training to make the most of not only labeled data but also unlabeled data.

A Study on Environmental Factor Recommendation Technology based on Deep Learning for Digital Agriculture (디지털 농업을 위한 딥러닝 기반의 환경 인자 추천 기술 연구)

  • Han-Jin Cho
    • Smart Media Journal
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    • v.12 no.5
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    • pp.65-72
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    • 2023
  • Smart Farm means creating new value in various fields related to agriculture, including not only agricultural production but also distribution and consumption through the convergence of agriculture and ICT. In Korea, a rental smart farm is created to spread smart agriculture, and a smart farm big data platform is established to promote data collection and utilization. It is pushing for digital transformation of agricultural products distribution from production areas to consumption areas, such as expanding smart APCs, operating online exchanges, and digitizing wholesale market transaction information. As such, although agricultural data is generated according to characteristics from various sources, it is only used as a service using statistics and standardized data. This is because there are limitations due to distributed data collection from agriculture to production, distribution, and consumption, and it is difficult to collect and process various types of data from various sources. Therefore, in this paper, we analyze the current state of domestic agricultural data collection and sharing for digital agriculture and propose a data collection and linkage method for artificial intelligence services. And, using the proposed data, we propose a deep learning-based environmental factor recommendation method.

Development of Career Management System with Rewarding Policy Considering the Ethereum Blockchain Performance (이더리움 블록체인의 성능을 고려한 보상정책을 갖는 이력관리 시스템 개발)

  • Jung-Min Hong;Ye-Jin Kim;Yu-Jeong Kim;Hye-Jeong Park;Eun-Seong Kang;Hyung-Jong Kim
    • Journal of the Korea Society for Simulation
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    • v.32 no.4
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    • pp.59-67
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    • 2023
  • Private blockchains can apply enhanced security policies that allow only authorized users to participate in the blockchain network. In addition, when used in a career management system where the validity of an individual's career is important, it has the suitable characteristics in terms of information integrity. However, due to the excessive performance requirements of blockchain technology, identifying performance characteristics through simulation can be helpful in stable operation of the system. This paper presents research results that utilized performance evaluation results while constructing a career management system based on the Ethereum blockchain. The service not only serves as a portfolio that records personal career development activities, certification acquisition, and award results, but also provides a community function for career planning to strengthen employment competitiveness. In addition, we present how a compensation policy can be executed to encourage users to participate in career development through community activities. In particular, an appropriate compensation policy was derived by reviewing changes in performance characteristics in accordance with the transaction volume on Geth nodes.

Model Interpretation through LIME and SHAP Model Sharing (LIME과 SHAP 모델 공유에 의한 모델 해석)

  • Yong-Gil Kim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.2
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    • pp.177-184
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    • 2024
  • In the situation of increasing data at fast speed, we use all kinds of complex ensemble and deep learning algorithms to get the highest accuracy. It's sometimes questionable how these models predict, classify, recognize, and track unknown data. Accomplishing this technique and more has been and would be the goal of intensive research and development in the data science community. A variety of reasons, such as lack of data, imbalanced data, biased data can impact the decision rendered by the learning models. Many models are gaining traction for such interpretations. Now, LIME and SHAP are commonly used, in which are two state of the art open source explainable techniques. However, their outputs represent some different results. In this context, this study introduces a coupling technique of LIME and Shap, and demonstrates analysis possibilities on the decisions made by LightGBM and Keras models in classifying a transaction for fraudulence on the IEEE CIS dataset.

A Study on Improvement Measures for Internal Controls in Cryptocurrency (가상자산 운영의 위험관리를 위한 내부통제 개선방안에 관한 연구)

  • Byoung Hoon Choi;JinYong Lee;Sam Hyun Chun
    • Convergence Security Journal
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    • v.24 no.3
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    • pp.51-57
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    • 2024
  • Cryptocurrency service providers and virtual asset operators, built on blockchain technology, face transaction risks such as cyber threats, wallet theft by internal personnel, theft of customers' private keys, and fraudulent cryptocurrency transfer signatures. To ensure secure operations against these threats, their security is validated through the ISMS-P certification. This study to analyze the risks presented in ISO TR 23576, which is specialized for cryptocurrency service providers and operators, in addition to the ISMS-P certification they obtain. The study will focus on the detailed inspection items of ISMS-P and ISO TR 23576 for cryptocurrency service providers and assess their importance. Based on this analysis, the study proposes an internal security control process for cryptocurrency service providers to address the top-priority risks, enabling practitioners to perform security control tasks more efficiently.

Smart-Coord: Enhancing Healthcare IoT-based Security by Blockchain Coordinate Systems

  • Talal Saad Albalawi
    • International Journal of Computer Science & Network Security
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    • v.24 no.8
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    • pp.32-42
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    • 2024
  • The Internet of Things (IoT) is set to transform patient care by enhancing data collection, analysis, and management through medical sensors and wearable devices. However, the convergence of IoT device vulnerabilities and the sensitivity of healthcare data raises significant data integrity and privacy concerns. In response, this research introduces the Smart-Coord system, a practical and affordable solution for securing healthcare IoT. Smart-Coord leverages blockchain technology and coordinate-based access management to fortify healthcare IoT. It employs IPFS for immutable data storage and intelligent Solidity Ethereum contracts for data integrity and confidentiality, creating a hierarchical, AES-CBC-secured data transmission protocol from IoT devices to blockchain repositories. Our technique uses a unique coordinate system to embed confidentiality and integrity regulations into a single access control model, dictating data access and transfer based on subject-object pairings in a coordinate plane. This dual enforcement technique governs and secures the flow of healthcare IoT information. With its implementation on the Matic network, the Smart-Coord system's computational efficiency and cost-effectiveness are unparalleled. Smart-Coord boasts significantly lower transaction costs and data operation processing times than other blockchain networks, making it a practical and affordable solution. Smart-Coord holds the promise of enhancing IoT-based healthcare system security by managing sensitive health data in a scalable, efficient, and secure manner. The Smart-Coord framework heralds a new era in healthcare IoT adoption, expertly managing data integrity, confidentiality, and accessibility to ensure a secure, reliable digital environment for patient data management.

An Edge Enabled Region-oriented DAG-based Distributed Ledger System for Secure V2X Communication

  • S. Thangam;S. Sibi Chakkaravarthy
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.8
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    • pp.2253-2280
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    • 2024
  • In the upcoming era of transportation, a groundbreaking technology, known as vehicle-to-everything (V2X) communication, is poised to redefine our driving experience and revolutionize traffic management. Real-time and secure communication plays a pivotal role in V2X networks, with the decision-making process being a key factor in establishing communication and determining malicious nodes. The proposed framework utilizes a directed acyclic graph (DAG) to facilitate real-time processing and expedite decision-making. This innovative approach ensures seamless connectivity among vehicles, the surrounding infrastructure, and various entities. To enhance communication efficiency, the entire roadside unit (RSU) region can be subdivided into various sub-regions, allowing RSUs to monitor and govern each sub-region. This strategic approach significantly reduces transaction approval time, thereby improving real-time communication. The framework incorporates a consensus mechanism to ensure robust security, even in the presence of malicious nodes. Recognizing the dynamic nature of V2X networks, the addition and removal of nodes are aligned. Communication latency is minimized through the deployment of computational resources near the data source and leveraging edge computing. This feature provides invaluable recommendations during critical situations that demand swift decision-making. The proposed architecture is further validated using the "veins" simulation tool. Simulation results demonstrate a remarkable success rate exceeding 95%, coupled with a significantly reduced consensus time compared to prevailing methodologies. This comprehensive approach not only addresses the evolving requirements of secure V2X communication but also substantiates practical success through simulation, laying the foundation for a transformative era in transportation.