58,414 research outputs found

    Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction

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    Assessing systemic risk in financial markets is of great importance but it often requires data that are unavailable or available at a very low frequency. For this reason, systemic risk assessment with partial information is potentially very useful for regulators and other stakeholders. In this paper we consider systemic risk due to fire sales spillover and portfolio rebalancing by using the risk metrics defined by Greenwood et al. (2015). By using the Maximum Entropy principle we propose a method to assess aggregated and single bank's systemicness and vulnerability and to statistically test for a change in these variables when only the information on the size of each bank and the capitalization of the investment assets are available. We prove the effectiveness of our method on 2001-2013 quarterly data of US banks for which portfolio composition is available.Comment: 36 pages, 6 figures, Accepted on Journal of Economic Dynamics and Contro

    Structural Vulnerability Analysis of Electric Power Distribution Grids

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    Power grid outages cause huge economical and societal costs. Disruptions in the power distribution grid are responsible for a significant fraction of electric power unavailability to customers. The impact of extreme weather conditions, continuously increasing demand, and the over-ageing of assets in the grid, deteriorates the safety of electric power delivery in the near future. It is this dependence on electric power that necessitates further research in the power distribution grid security assessment. Thus measures to analyze the robustness characteristics and to identify vulnerabilities as they exist in the grid are of utmost importance. This research investigates exactly those concepts- the vulnerability and robustness of power distribution grids from a topological point of view, and proposes a metric to quantify them with respect to assets in a distribution grid. Real-world data is used to demonstrate the applicability of the proposed metric as a tool to assess the criticality of assets in a distribution grid

    Assessment of Source Code Obfuscation Techniques

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    Obfuscation techniques are a general category of software protections widely adopted to prevent malicious tampering of the code by making applications more difficult to understand and thus harder to modify. Obfuscation techniques are divided in code and data obfuscation, depending on the protected asset. While preliminary empirical studies have been conducted to determine the impact of code obfuscation, our work aims at assessing the effectiveness and efficiency in preventing attacks of a specific data obfuscation technique - VarMerge. We conducted an experiment with student participants performing two attack tasks on clear and obfuscated versions of two applications written in C. The experiment showed a significant effect of data obfuscation on both the time required to complete and the successful attack efficiency. An application with VarMerge reduces by six times the number of successful attacks per unit of time. This outcome provides a practical clue that can be used when applying software protections based on data obfuscation.Comment: Post-print, SCAM 201

    Towards Validating Risk Indicators Based on Measurement Theory (Extended version)

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    Due to the lack of quantitative information and for cost-efficiency, most risk assessment methods use partially ordered values (e.g. high, medium, low) as risk indicators. In practice it is common to validate risk indicators by asking stakeholders whether they make sense. This way of validation is subjective, thus error prone. If the metrics are wrong (not meaningful), then they may lead system owners to distribute security investments inefficiently. For instance, in an extended enterprise this may mean over investing in service level agreements or obtaining a contract that provides a lower security level than the system requires. Therefore, when validating risk assessment methods it is important to validate the meaningfulness of the risk indicators that they use. In this paper we investigate how to validate the meaningfulness of risk indicators based on measurement theory. Furthermore, to analyze the applicability of the measurement theory to risk indicators, we analyze the indicators used by a risk assessment method specially developed for assessing confidentiality risks in networks of organizations

    Using the Asian Knowledge Model “APO” as a Determinant for Performance Excellence in Universities- Empirical Study at Al -Azhar University- Gaza

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    This study aims to use the Asian knowledge model “APO” as a determinant for performance excellence in universities and identifying the most effecting factors on it. This study was applied on Al-Azhar University in Gaza strip. The result of the study showed that (APO) model is valid as a measure and there are four dimensions in the model affecting significantly more than the others (university processes, KM leadership, personnel, KM outputs). Furthermore, performance excellence produced though modernizing the means of education, curriculum development, technology and flexibility in the organizational structure. The study recommends expanding the usage of (APO) model, enhancing the role of knowledge leadership, technology, organizational flexibility, sharing culture and incentive systems that encouraging innovation

    Prioritising the best use of biomass resources: conceptualising trade-offs

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    02.09.13 KB. Ok to add report to Spiral. Authors hold copyrightUsing biomass to provide energy services is one of the most versatile options for increasing the proportion of renewable energy in the existing system. This report reviews metrics used to compare alternative bio-energy pathways and identifies limitations inherent in the way that they are calculated and interpreted. It also looks at how companies and investors approach strategic decisions in the bio-energy area. Bio-energy pathways have has physical and economic attributes that can be measured or modelled. These include: the capital cost, operating cost, emissions to air, land and water. Conceptually, comparing alternative pathways is as simple as selecting the attributes and metrics you consider to be most important and ranking the alternative pathways accordingly. At an abstract level there is good agreement about which features of bio-energy pathways are desirable, but there is little agreement about which performance metrics best capture all the relevant information about a bio-energy pathway. Between studies there is also a great deal of variation and this impedes comparison. Common metrics describe energetic performance, economic performance, environmental performance (emissions, land and water use), and social and ecological performance. Compound metrics may be used to integrate multiple attributes but their highly aggregate nature may make them difficult to interpret. Insights that may be drawn from the analysis include:
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