ESPOONERBAC_{{ERBAC}}: Enforcing Security Policies In Outsourced Environments

Data outsourcing is a growing business model offering services to individuals and enterprises for processing and storing a huge amount of data. It is not only economical but also promises higher availability, scalability, and more effective quality of service than in-house solutions. Despite all its benefits, data outsourcing raises serious security concerns for preserving data confidentiality. There are solutions for preserving confidentiality of data while supporting search on the data stored in outsourced environments. However, such solutions do not support access policies to regulate access to a particular subset of the stored data. For complex user management, large enterprises employ Role-Based Access Controls (RBAC) models for making access decisions based on the role in which a user is active in. However, RBAC models cannot be deployed in outsourced environments as they rely on trusted infrastructure in order to regulate access to the data. The deployment of RBAC models may reveal private information about sensitive data they aim to protect. In this paper, we aim at filling this gap by proposing \textbf{$\mathit{ESPOON_{ERBAC}}$} for enforcing RBAC policies in outsourced environments. $\mathit{ESPOON_{ERBAC}}$ enforces RBAC policies in an encrypted manner where a curious service provider may learn a very limited information about RBAC policies. We have implemented $\mathit{ESPOON_{ERBAC}}$ and provided its performance evaluation showing a limited overhead, thus confirming viability of our approach.Comment: The final version of this paper has been accepted for publication in Elsevier Computers & Security 2013. arXiv admin note: text overlap with arXiv:1306.482

Spatial Guilds in the Serengeti Food Web Revealed by a Bayesian Group Model

Food webs, networks of feeding relationships among organisms, provide fundamental insights into mechanisms that determine ecosystem stability and persistence. Despite long-standing interest in the compartmental structure of food webs, past network analyses of food webs have been constrained by a standard definition of compartments, or modules, that requires many links within compartments and few links between them. Empirical analyses have been further limited by low-resolution data for primary producers. In this paper, we present a Bayesian computational method for identifying group structure in food webs using a flexible definition of a group that can describe both functional roles and standard compartments. The Serengeti ecosystem provides an opportunity to examine structure in a newly compiled food web that includes species-level resolution among plants, allowing us to address whether groups in the food web correspond to tightly-connected compartments or functional groups, and whether network structure reflects spatial or trophic organization, or a combination of the two. We have compiled the major mammalian and plant components of the Serengeti food web from published literature, and we infer its group structure using our method. We find that network structure corresponds to spatially distinct plant groups coupled at higher trophic levels by groups of herbivores, which are in turn coupled by carnivore groups. Thus the group structure of the Serengeti web represents a mixture of trophic guild structure and spatial patterns, in contrast to the standard compartments typically identified in ecological networks. From data consisting only of nodes and links, the group structure that emerges supports recent ideas on spatial coupling and energy channels in ecosystems that have been proposed as important for persistence.Comment: 28 pages, 6 figures (+ 3 supporting), 2 tables (+ 4 supporting

The use of multilayer network analysis in animal behaviour

Network analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as \emph{multilayer network analysis}, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour as connected 'layers' of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population, and evolutionary levels of organisation. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer network analysis.Comment: Thoroughly revised; title changed slightl

Collaborative design : managing task interdependencies and multiple perspectives

This paper focuses on two characteristics of collaborative design with respect to cooperative work: the importance of work interdependencies linked to the nature of design problems; and the fundamental function of design cooperative work arrangement which is the confrontation and combination of perspectives. These two intrinsic characteristics of the design work stress specific cooperative processes: coordination processes in order to manage task interdependencies, establishment of common ground and negotiation mechanisms in order to manage the integration of multiple perspectives in design

The actinobacterial transcription factor RbpA binds to the principal sigma subunit of RNA polymerase

RbpA is a small non-DNA-binding transcription factor that associates with RNA polymerase holoenzyme and stimulates transcription in actinobacteria, including Streptomyces coelicolor and Mycobacterium tuberculosis. RbpA seems to show specificity for the vegetative form of RNA polymerase as opposed to alternative forms of the enzyme. Here, we explain the basis of this specificity by showing that RbpA binds directly to the principal σ subunit in these organisms, but not to more diverged alternative σ factors. Nuclear magnetic resonance spectroscopy revealed that, although differing in their requirement for structural zinc, the RbpA orthologues from S. coelicolor and M. tuberculosis share a common structural core domain, with extensive, apparently disordered, N- and C-terminal regions. The RbpA-σ interaction is mediated by the C-terminal region of RbpA and σ domain 2, and S. coelicolor RbpA mutants that are defective in binding σ are unable to stimulate transcription in vitro and are inactive in vivo. Given that RbpA is essential in M. tuberculosis and critical for growth in S. coelicolor, these data support a model in which RbpA plays a key role in the σ cycle in actinobacteria

Work and Home Location: Possible Role of Social Networks

This research explores to what extent people's work locations are similar to that of those who live around them. Using the Longitudinal Economic and Household Dynamics data set and the US census for the Twin Cities (Minneapolis-St. Paul) metropolitan area, we investigate the home and work locations of different census block residents. Our aim is to investigate if people who live close to one another, also work close to one another to a degree beyond what would be expected at random. We find a significantly non-random correlation between joint home and joint work locations. Further, we show what features of particular neighborhoods are associated with comparatively higher incidences of people sharing work locations. One reason for such an outcome can be the role neighborhood level social networks play in locating jobs; or conversely work place social networks play in choosing the home location or both. Such findings should be used to refine work trip distribution models that otherwise depend mainly on impedance between the origin and destination.Social Networks, Trip Distribution, Destination Choice, Work, Commuting, Residential Location

A Mechanism for Dynamic Coordination of Multiple Robots

In this paper, we present a mechanism for coordinating multiple robots in the execution of cooperative tasks. The basic idea in the paper is to assign to each robot in the team, a role that determines its actions during the cooperation. The robots dynamically assume and exchange roles in a synchronized manner in order to perform the task successfully, adapting to unexpected events in the environment. We model this mechanism using a hybrid systems framework and apply it in different cooperative tasks: cooperative manipulation and cooperative search and transportation. Simulations and real experiments demonstrating the effectiveness of the proposed mechanism are presented