Assured Information Security (United States)

The place of alcohol in Abu Dhabi, capital of the United Arab Emirates, has undergone fast-paced changes over the last decade. While drinking was initially restricted to hotels, it is now possible to engage in this practice publicly; and alcohol has become central within the new leisure and entertainment districts. This paper argues that such evolutions reflect shifting representations of alcohol in the state’s discourse. Whereas it had first been constructed as a ‘necessary evil,’ an exogeneous substance required to cater to the needs of a growing foreign workforce, alcohol is now portrayed as a primary feature of the world-class city. These transformations draw a moral geography of the capital which produces specific norms: at the same time as they serve Abu Dhabi’s ambitions to become a ‘global destination’ for international tourists, and for the expatriate ‘talents’ who will serve the state’s project of economic diversification, they exclude from the making of the world-class city those (both citizens and non-citizens) who are not at ease with such changes.

19.0.1 (2021-07-27) Bug Fixes <strong>SynchronizableRenderWindow:</strong> Add support for vtkCubeAxesActor and vtkScalarBarActor (ac6d947)

Marine fisheries represent a social-ecological system driven by both complex ecological processes and human interactions. Ecosystem-based fisheries management requires an understanding of both the biological and social components, and management failure can occur when either are excluded. Despite the significance of both, most research has focused on characterizing biological uncertainty rather than on better understanding the impacts of human behavior because of the difficulty of incorporating human behavior into simulation models. In this study, we use the fisheries in Narragansett Bay (Rhode Island, USA) as a case study to demonstrate how coupled modeling can be used to represent interactions between the food web and fishers in a social-ecological system. Narragansett Bay holds both a commercial fishery for forage fish, i.e., Atlantic menhaden (Brevoortia tyrannus) and a recreational fishery for their predators, i.e. striped bass (Morone saxatilis) and bluefish (Pomatomus saltatrix). To explore trade-offs between these two fisheries, we created a food web model and then coupled it to a recreational fishers' behavior model, creating a dynamic social-ecological representation of the ecosystem. Fish biomass was projected until 2030 in both the stand-alone food web model and the coupled social-ecological model, with results highlighting how the incorporation of fisher behavior in modeling can lead to changes in the ecosystem. We examined how model outputs varied in response to three attributes: (1) the forage fish commercial harvest scenario, (2) the predatory (piscivorous) fish abundance-catch relationship in the recreational fishery, and (3) the rate at which recreational fishers become discouraged (termed "satisfaction loss"). Higher commercial harvest of forage fish led to lower piscivorous fish biomass but had minimal effects on the number of piscivorous fish caught recreationally or recreational fisher satisfaction. Both the abundance-catch relationship and satisfaction loss rate had notable effects on the fish biomass, the number of fish caught recreationally, and recreational fisher satisfaction. Currently, the lack of spatial and location-specific fisher behavior data limits the predictive use of our model. However, our modeling framework shows that fisher behavior can be successfully incorporated into a coupled social-ecological model through the use of agent-based modeling, and our results highlight that its inclusion can influence ecosystem dynamics. Because fisher decision making and the ecosystem can influence one another, social responses to changing ecosystems should be explicitly integrated into ecosystem modeling to improve ecosystem-based fisheries management efforts.

We study an important yet under-addressed problem of quickly and safely improving policies in online reinforcement learning domains. As its solution, we propose a novel exploration strategy - diverse exploration (DE), which learns and deploys a diverse set of safe policies to explore the environment. We provide DE theory explaining why diversity in behavior policies enables effective exploration without sacrificing exploitation. Our empirical study shows that an online policy improvement algorithm framework implementing the DE strategy can achieve both fast policy improvement and safe online performance.

Due to the high consequences of poorly performing automated insider threat detection systems (ITDSs), it is advantageous for Government and commercial organizations to understand the performance and limitations of potential systems before their deployment. We propose to capture the uncertainties and dynamics of organizations deploying ITDSs to create an accurate and effective probabilistic graphical model that forecasts the operational performance of an ITDS throughout its deployment. Ultimately, we believe this modeling methodology will result in the deployment of more effective ITDSs.

Modern cyber attacks are often conducted by distributing digital documents that contain malware. The approach detailed herein, which consists of a classifier that uses features derived from dynamic analysis of a document viewer as it renders the document in question, is capable of classifying the disposition of digital documents with greater than 98% accuracy even when its model is trained on just small amounts of data. To keep the classification model itself small and thereby to provide scalability, we employ an entity resolution strategy that merges syntactically disparate features that are thought to be semantically equivalent but vary due to programmatic randomness. Entity resolution enables construction of a comprehensive model of benign functionality using relatively few training documents, and the model does not improve significantly with additional training data.

Preliminary experiment design and research goals are presented to measure the security implications of using just-in-time (JIT) compilation in conjunction with hardware-enforced restrictions on the computational complexity of general purpose applications. LLVM passes are used during compilation to mark sub-components of an application if they are provably halting (Walter recursive). A modified JIT engine is under development to unroll loops based on run-time semantics, while Intel's Processor Tracing technology is used to enforce those execution bounds. This paper describes an ongoing effort to improve security through the realization and enforcement of restricted computational environments. As an example, an analysis of the impact on the attacker when return-oriented programming is limited to unidirectional execution highlights one such computationally-derived security benefit of this work.

This article describes the deployment of a next generation 9-1-1 network in Southern Illinois. Thirteen counties and one municipality banded together to design, build, test and deploy this network, which provides voice, text, video and data services to emergency callers, call takers, and first responders. The author describes key challenges where contributions have been and will continue to be made through the collaboration of industry, academia, government, and standards bodies. Lessons learned and potential next steps are examined.

Cross-site scripting XSS vulnerabilities are among the most prevailing problems on the web. Among the practically deployed countermeasures is adefense-in-depth Content Security Policy CSP to mitigate the effects of XSS attacks. However, the adoption of CSP has been frustratingly slow. This paper focuses on a particular roadblock for wider adoption of CSP: its interplay with browser extensions. We report on a large-scale empirical study of all free extensions from Google's Chrome web store that uncovers three classes of vulnerabilities arising from the tension between the power of extensions and CSP intended by web pages: third party code inclusion, enabling XSS, and user profiling. We discover extensions with over a million users in each vulnerable category. With the goal to facilitate a wider adoption of CSP, we propose an extension-aware CSP endorsement mechanism between the server and client. A case study with the Rapportive extensions for Firefox and Chrome demonstrates the practicality of the approach.

The IS 2010 report is the latest output from model curriculum work for Information Systems (IS) that began in the early 1970s. Prior to this current effort, the most recent version of the IS undergraduate model curriculum is IS 2002 (Gorgone et al., 2003), published in early 2003. IS 2002 was a relatively minor update of IS'97 (Davis et al., 1997). Both IS 2002 and IS '97 were joint efforts by ACM, AIS, and DPMA/AITP (Data Processing Management Association/ Association of Information Technology Professionals). IS'97 was preceded by DPMA'90 (Longenecker and Feinstein 1991) and ACM Curriculum Recommendations 1983 (ACM 1983) and 1973 (Couger 1973). IS 2002 has been widely accepted and it has also been the basis for accreditation of undergraduate programs of Information Systems. This report represents the combined effort of numerous individuals and reflects the interests of thousands of faculty and practitioners. It is grounded in the expected requirements of industry, represents the views of organizations employing the graduates, and is supported by other IS-related organizations.