• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.246-250
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• 2008

This paper presents the design of network vulnerability analysis system which can integrate various vulnerability assessment tools to improve the preciseness of the vulnerability scan result. Manual checking method performed by a security expert is the most precise and safe way. But this is not appropriate for the large-scale network which has a lot of systems and network devices. Therefore automatic scanning tool is recommended for fast and convenient use. The scanning targets may be different according to the kind of vulnerability scanners, or otherwise even for the same scanning target, the scanning items and the scanning results may be different by each vulnerability scanner, Accordingly, there are the cases in which various scanners, instead of a single scanner, are simultaneously utilized with the purpose of complementing each other. However, in the case of simultaneously utilizing various scanners on the large-scale network, the integrative analysis and relevance analysis on vulnerability information by a security manager becomes time-consumable or impossible. The network vulnerability analysis system suggested in this paper provides interface which allows various vulnerability assessment tools to easily be integrated, common policy which can be applied for various tools at the same time, and automated integrative process.

• Asia pacific journal of information systems
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• v.8 no.2
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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.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.26 no.2
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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.