• Title/Summary/Keyword: 내부자 공격

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Security Knowledge Classification Framework for Future Intelligent Environment (미래 융합보안 인력양성을 위한 보안교육과정 분류체계 설계)

  • Na, Onechul;Lee, Hyojik;Sung, Soyung;Chang, Hangbae
    • The Journal of Society for e-Business Studies
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    • v.20 no.3
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    • pp.47-58
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    • 2015
  • Recently, new information security vulnerabilities have proliferated with the convergence of information security environments and information and communication technology. Accordingly, new types of cybercrime are on the rise, and security breaches and other security-related incidents are increasing rapidly because of security problems like external cyberattacks, leakage by insiders, etc. These threats will continue to multiply as industry and technology converge. Thus, the main purpose of this paper is to design and present security subjects in order to train professional security management talent who can deal with the enhanced threat to information. To achieve this, the study first set key information security topics for business settings on the basis of an analysis of preceding studies and the results of a meeting of an expert committee. The information security curriculum taxonomy is developed with reference to an information security job taxonomy for domestic conditions in South Korea. The results of this study are expected to help train skilled security talent who can address new security threats in the future environment of industrial convergence.

Industrial Technology Leak Detection System on the Dark Web (다크웹 환경에서 산업기술 유출 탐지 시스템)

  • Young Jae, Kong;Hang Bae, Chang
    • Smart Media Journal
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    • v.11 no.10
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    • pp.46-53
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    • 2022
  • Today, due to the 4th industrial revolution and extensive R&D funding, domestic companies have begun to possess world-class industrial technologies and have grown into important assets. The national government has designated it as a "national core technology" in order to protect companies' critical industrial technologies. Particularly, technology leaks in the shipbuilding, display, and semiconductor industries can result in a significant loss of competitiveness not only at the company level but also at the national level. Every year, there are more insider leaks, ransomware attacks, and attempts to steal industrial technology through industrial spy. The stolen industrial technology is then traded covertly on the dark web. In this paper, we propose a system for detecting industrial technology leaks in the dark web environment. The proposed model first builds a database through dark web crawling using information collected from the OSINT environment. Afterwards, keywords for industrial technology leakage are extracted using the KeyBERT model, and signs of industrial technology leakage in the dark web environment are proposed as quantitative figures. Finally, based on the identified industrial technology leakage sites in the dark web environment, the possibility of secondary leakage is detected through the PageRank algorithm. The proposed method accepted for the collection of 27,317 unique dark web domains and the extraction of 15,028 nuclear energy-related keywords from 100 nuclear power patents. 12 dark web sites identified as a result of detecting secondary leaks based on the highest nuclear leak dark web sites.