Cluster-based Vulnerability Assessment Applied to Operating Systems

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs: Windows, Mac, IOS, and Linux. For the OSs analyzed in terms of curve fitting and prediction capability, our results, compared to a power-law model without clustering issued from a family of SRMs, are more accurate in all cases we analyzed

Cluster-based Vulnerability Assessment Applied to Operating Systems

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs: Windows, Mac, IOS, and Linux. For the OSs analyzed in terms of curve fitting and prediction capability, our results, compared to a power-law model without clustering issued from a family of SRMs, are more accurate in all cases we analyzed

Efficient Database Generation for Data-driven Security Assessment of Power Systems

Power system security assessment methods require large datasets of operating points to train or test their performance. As historical data often contain limited number of abnormal situations, simulation data are necessary to accurately determine the security boundary. Generating such a database is an extremely demanding task, which becomes intractable even for small system sizes. This paper proposes a modular and highly scalable algorithm for computationally efficient database generation. Using convex relaxation techniques and complex network theory, we discard large infeasible regions and drastically reduce the search space. We explore the remaining space by a highly parallelizable algorithm and substantially decrease computation time. Our method accommodates numerous definitions of power system security. Here we focus on the combination of N-k security and small-signal stability. Demonstrating our algorithm on IEEE 14-bus and NESTA 162-bus systems, we show how it outperforms existing approaches requiring less than 10% of the time other methods require.Comment: Database publicly available at: https://github.com/johnnyDEDK/OPs_Nesta162Bus - Paper accepted for publication at IEEE Transactions on Power System

DCDIDP: A distributed, collaborative, and data-driven intrusion detection and prevention framework for cloud computing environments

With the growing popularity of cloud computing, the exploitation of possible vulnerabilities grows at the same pace; the distributed nature of the cloud makes it an attractive target for potential intruders. Despite security issues delaying its adoption, cloud computing has already become an unstoppable force; thus, security mechanisms to ensure its secure adoption are an immediate need. Here, we focus on intrusion detection and prevention systems (IDPSs) to defend against the intruders. In this paper, we propose a Distributed, Collaborative, and Data-driven Intrusion Detection and Prevention system (DCDIDP). Its goal is to make use of the resources in the cloud and provide a holistic IDPS for all cloud service providers which collaborate with other peers in a distributed manner at different architectural levels to respond to attacks. We present the DCDIDP framework, whose infrastructure level is composed of three logical layers: network, host, and global as well as platform and software levels. Then, we review its components and discuss some existing approaches to be used for the modules in our proposed framework. Furthermore, we discuss developing a comprehensive trust management framework to support the establishment and evolution of trust among different cloud service providers. © 2011 ICST

Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches

Security issues related to vulnerability assessment in electrical networks are necessary for operators to identify the critical branches. At present, using complex network theory to assess the structural vulnerability of the electrical network is a popular method. However, the complex network theory cannot be comprehensively applicable to the operational vulnerability assessment of the electrical network because the network operation is closely dependent on the physical rules not only on the topological structure. To overcome the problem, an adjacent graph (AG) considering the topological, physical, and operational features of the electrical network is constructed to replace the original network. Through the AG, a branch importance index that considers both the importance of a branch and the fault adjacent relationships among branches is constructed to evaluate the electrical network vulnerability. The IEEE 118-bus system and the French grid are employed to validate the effectiveness of the proposed method.National Natural Science Foundation of China under Grant U1734202National Key Research and Development Plan of China under Grant 2017YFB1200802-12National Natural Science Foundation of China under Grant 51877181National Natural Science Foundation of China under Grant 61703345Chinese Academy of Sciences, under Grant 2018-2019-0

Broadacre farmers adapting to a changing climate

Abstract Data on the financial performance of a diverse set of 249 farm businesses in south-western Australia over the period 2002 to 2011 was collated and analysed.  These 10 years were a period of challenging weather years, underpinned by a warming and drying trend in the region’s climate, frost events and marked price volatility.Based on a range of metrics, almost two-thirds (64%) of the farms in the sample were classed as growing or strong. A less secure group of farms that are at some potential financial risk formed 15% of the farm sample. Over the study period farm profitability, on average, improved, supported by productivity growth, in spite of no underlying improvement in the farmers’ terms of trade.  Productivity improvement allowed most farm businesses, especially crop and mixed enterprise farm businesses, to prosper.  The pathway to their profitability was not so much by investing in new technologies that may have shifted outwards farms’ production possibilities, but rather through better use of existing technologies, including technologies that offered scale economies. Also farmers’ shift into greater dependence on cropping, especially wheat production, was shown to be a sensible and successful adaptation strategy in many regions of south-western Australia, particularly the northern grainbelt.The unique and particular characteristics of each farm business were the main determinant of their business success.  However, a few generalisations apply.  Due to seasonal and market conditions during the study period more farms in the northern parts of the grainbelt in south-western Australia fared better.  Also farmers whose businesses grew strongly over the study period on average displayed superior management capabilities and choices in many areas of farm management.  In addition, these farmers were often more connected to their local community and achieved greater work-life balance.We conclude that as long as broadacre farmers in south-western Australia have on-going access to improved crop varieties and technologies that support the profitable growing of crops, especially wheat; and that they have access to farm management and business education then farmers are likely to be able to adapt to projected climate change.  Provided that a farmer’s terms of trade does not become unduly adverse, and that farmers sensibly manage farm debt, then it seems highly likely that farmers who continue to rely on crop production, mostly wheat-growing, will persist as financially sound businesses in most parts of the study region, even in the face of projected climate change.Please cite this report as:Kingwell, R, Anderton, L, Islam, N, Xayavong, V, Wardell-Johnson, A, Feldman, D, Speijers, J 2013 Broadacre farmers adapting to a changing climate, National Climate Change Adaptation Research Facility, Gold Coast. pp.171.Data on the financial performance of a diverse set of 249 farm businesses in south-western Australia over the period 2002 to 2011 was collated and analysed.  These 10 years were a period of challenging weather years, underpinned by a warming and drying trend in the region’s climate, frost events and marked price volatility.Based on a range of metrics, almost two-thirds (64%) of the farms in the sample were classed as growing or strong. A less secure group of farms that are at some potential financial risk formed 15% of the farm sample. Over the study period farm profitability, on average, improved, supported by productivity growth, in spite of no underlying improvement in the farmers’ terms of trade.  Productivity improvement allowed most farm businesses, especially crop and mixed enterprise farm businesses, to prosper.  The pathway to their profitability was not so much by investing in new technologies that may have shifted outwards farms’ production possibilities, but rather through better use of existing technologies, including technologies that offered scale economies. Also farmers’ shift into greater dependence on cropping, especially wheat production, was shown to be a sensible and successful adaptation strategy in many regions of south-western Australia, particularly the northern grainbelt.The unique and particular characteristics of each farm business were the main determinant of their business success.  However, a few generalisations apply.  Due to seasonal and market conditions during the study period more farms in the northern parts of the grainbelt in south-western Australia fared better.  Also farmers whose businesses grew strongly over the study period on average displayed superior management capabilities and choices in many areas of farm management.  In addition, these farmers were often more connected to their local community and achieved greater work-life balance.We conclude that as long as broadacre farmers in south-western Australia have on-going access to improved crop varieties and technologies that support the profitable growing of crops, especially wheat; and that they have access to farm management and business education then farmers are likely to be able to adapt to projected climate change.  Provided that a farmer’s terms of trade does not become unduly adverse, and that farmers sensibly manage farm debt, then it seems highly likely that farmers who continue to rely on crop production, mostly wheat-growing, will persist as financially sound businesses in most parts of the study region, even in the face of projected climate change