• 제목/요약/키워드: integrative vulnerability analysis

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다양한 취약점 점검 도구를 이용한 자동화된 네트워크 취약점 통합 분석 시스템 설계 (An Automatic Network Vulnerability Analysis System using Multiple Vulnerability Scanners)

  • 윤준;심원태
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제14권2호
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    • pp.246-250
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    • 2008
  • 본 논문에서는 네트워크 취약점 분석 결과의 정확성을 향상시키기 위한 방법으로 다양한 취약점 점검 도구를 통합할 수 있는 네트워크 취약점 자동 분석 시스템을 제안한다. 일반적으로 전문가에 의한 수동 점검이 가장 정확한 취약점 점검 방법으로 평가되지만, 복잡하고 규모가 큰 네트워크의 경우 효율적인 취약점 분석을 위해 자동화된 네트워크 취약점 점검 도구를 활용한다. 그런데 취약점점검 도구의 종류에 따라 점검 대상이 다르거나 동일한 점검 대상에 대해서도 점검 항목과 점검 결과가 다를 수가 있어, 상호보완적인 목적으로 몇 개의 취약점 점검 도구를 동시에 사용하는 것이 효과적이다. 그러나 취약점 점검 도구들의 점검 결과에 대한 연관성 분석과 통합 분석에는 사람에 의한 수동적인 분석 작업이 필요하기 때문에, 이것은 상당히 시간 소모적인 작업이 되고 네트워크의 규모에 따라 통합 분석이 불가능하기도 하다. 본 논문에서는 다양한 취약점 점검 도구를 통합할 수 있는 인터페이스를 제공하고, 공통의 점검 정책 수립과 통합 분석의 자동화를 특징으로 하는 네트워크 취약점 통합 분석 시스템을 제안한다.

정보시스템의 위험도 분석에 관한 연구: 통합적인 분석 틀을 중심으로 (Risk Analysis for Information Systems: An Integrative Framework)

  • 김영걸;이종만;이재남
    • Asia pacific journal of information systems
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    • 제8권2호
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    • pp.37-51
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    • 1998
  • This study attempts to draw a blueprint of risk analysis for Information Systems (IS). We introduce two main variables for measuring IS risk - business-impact intensity and IS-vulnerability index - through the investigation of information characteristics, business processes and human-related factors. IS-vulnerability index consists of two factors such as degree of openness and degree of preparedness to the threats. Based on these factors, we built two integrative frameworks for risk analysis and management: One is a conceptual framework to enhance the understandability of IS risk itself; the other is an integrative framework to improve the managerial insight of overall IS risk. We then conducted a field study to empirically validate the proposed framework using a structural equations modeling method. We found that IS maturity and business-impact intensity were positively correlated to degree of openness to the threats, while IS maturity was negatively correlated to degree of preparedness to the threats.

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A Pilot Study Exploring Temporal Development of Gut Microbiome/Metabolome in Breastfed Neonates during the First Week of Life

  • Imad Awan;Emily Schultz;John D. Sterrett;Lamya'a M. Dawud;Lyanna R. Kessler;Deborah Schoch;Christopher A. Lowry;Lori Feldman-Winter;Sangita Phadtare
    • Pediatric Gastroenterology, Hepatology & Nutrition
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    • 제26권2호
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    • pp.99-115
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    • 2023
  • Purpose: Exclusive breastfeeding promotes gut microbial compositions associated with lower rates of metabolic and autoimmune diseases. Its cessation is implicated in increased microbiome-metabolome discordance, suggesting a vulnerability to dietary changes. Formula supplementation is common within our low-income, ethnic-minority community. We studied exclusively breastfed (EBF) neonates' early microbiome-metabolome coupling in efforts to build foundational knowledge needed to target this inequality. Methods: Maternal surveys and stool samples from seven EBF neonates at first transitional stool (0-24 hours), discharge (30-48 hours), and at first appointment (days 3-5) were collected. Survey included demographics, feeding method, medications, medical history and tobacco and alcohol use. Stool samples were processed for 16S rRNA gene sequencing and lipid analysis by gas chromatography-mass spectrometry. Alpha and beta diversity analyses and Procrustes randomization for associations were carried out. Results: Firmicutes, Proteobacteria, Bacteroidetes and Actinobacteria were the most abundant taxa. Variation in microbiome composition was greater between individuals than within (p=0.001). Palmitic, oleic, stearic, and linoleic acids were the most abundant lipids. Variation in lipid composition was greater between individuals than within (p=0.040). Multivariate composition of the metabolome, but not microbiome, correlated with time (p=0.030). Total lipids, saturated lipids, and unsaturated lipids concentrations increased over time (p=0.012, p=0.008, p=0.023). Alpha diversity did not correlate with time (p=0.403). Microbiome composition was not associated with each samples' metabolome (p=0.450). Conclusion: Neonate gut microbiomes were unique to each neonate; respective metabolome profiles demonstrated generalizable temporal developments. The overall variability suggests potential interplay between influences including maternal breastmilk composition, amount consumed and living environment.