Value-driven Security Agreements in Extended Enterprises

Today organizations are highly interconnected in business networks called extended enterprises. This is mostly facilitated by outsourcing and by new economic models based on pay-as-you-go billing; all supported by IT-as-a-service. Although outsourcing has been around for some time, what is now new is the fact that organizations are increasingly outsourcing critical business processes, engaging on complex service bundles, and moving infrastructure and their management to the custody of third parties. Although this gives competitive advantage by reducing cost and increasing flexibility, it increases security risks by eroding security perimeters that used to separate insiders with security privileges from outsiders without security privileges. The classical security distinction between insiders and outsiders is supplemented with a third category of threat agents, namely external insiders, who are not subject to the internal control of an organization but yet have some access privileges to its resources that normal outsiders do not have. Protection against external insiders requires security agreements between organizations in an extended enterprise. Currently, there is no practical method that allows security officers to specify such requirements. In this paper we provide a method for modeling an extended enterprise architecture, identifying external insider roles, and for specifying security requirements that mitigate security threats posed by these roles. We illustrate our method with a realistic example

Counting Change: Measuring Health Care Prices, Costs, and Spending

Considers the accuracy and utility of current data on the determinants of healthcare costs, distorting factors that make measuring the costs of healthcare delivery difficult, the benefits of cost and spending measurement, and efforts to develop measures

Consumer side resource accounting in cloud computing

PhD ThesisCloud computing services made available to consumers range from providing basic computational resources such as storage and compute power to sophisticated enterprise application services. A common business model is to charge consumers on a pay-per-use basis where they periodically pay for the resources they have consumed. The provider is responsible for measuring and collecting the resource usage data. This approach is termed provider-side accounting. A serious limitation of this approach is that consumers have no choice but to take whatever usage data that is made available by the provider as trustworthy. This thesis investigates whether it is possible to perform consumer-side resource accounting where a consumer independently collects, for a given cloud service, all the data required for calculating billing charges. If this were possible, then consumers will be able to perform reasonableness checks on the resource usage data available from service providers as well as raise alarms when apparent discrepancies are suspected in consumption figures. Two fundamental resources of cloud computing, namely, storage and computing are evaluated. The evaluation exercise reveals that the resource accounting models of popular cloud service providers, such as Amazon, are not entirely suited to consumer-side resource accounting, in that discrepancies between the data collected by the provider and the consumer can occur. The thesis precisely identifies the causes that could lead to such discrepancies and points out how the discrepancies can be resolved. The results from the thesis can be used by service providers to improve their resource accounting models. In particular, the thesis shows how an accounting model can be made strongly consumer–centric so that all the data that the model requires for calculating billing charges can be collected independently by the consumer. Strongly consumer–centric accounting models have the desirable property of openness and transparency, since service users are in a position to verify the charges billed to them.Cultural Affairs Department, Libyan Embassy, Londo

Reframing Agribusiness: Moving from Farm to Market Centric

Agribusiness is moving from farm to market centric, where effective activities anticipate and respond to customers, markets, and the systems in which they function. This evolution requires a broader conceptualization and more accurate definition, to convey a more dynamic, systemic, and integrative discipline, which increasingly is committed to value creation and the sustainable orchestration of food, fiber, and renewable resources. We discuss the forces driving this shift to the market, offer a new and more representative definition of agribusiness, provide models to illustrate some of the most compelling trends, and articulate key elements and implications of those models.agribusiness definition, conceptual models, market centric, market systems, Agribusiness, Marketing, Production Economics,

Cloud Index Tracking: Enabling Predictable Costs in Cloud Spot Markets

Cloud spot markets rent VMs for a variable price that is typically much lower than the price of on-demand VMs, which makes them attractive for a wide range of large-scale applications. However, applications that run on spot VMs suffer from cost uncertainty, since spot prices fluctuate, in part, based on supply, demand, or both. The difficulty in predicting spot prices affects users and applications: the former cannot effectively plan their IT expenditures, while the latter cannot infer the availability and performance of spot VMs, which are a function of their variable price. To address the problem, we use properties of cloud infrastructure and workloads to show that prices become more stable and predictable as they are aggregated together. We leverage this observation to define an aggregate index price for spot VMs that serves as a reference for what users should expect to pay. We show that, even when the spot prices for individual VMs are volatile, the index price remains stable and predictable. We then introduce cloud index tracking: a migration policy that tracks the index price to ensure applications running on spot VMs incur a predictable cost by migrating to a new spot VM if the current VM's price significantly deviates from the index price.Comment: ACM Symposium on Cloud Computing 201