CRiBAC: Community-centric role interaction based access control model

As one of the most efficient solutions to complex and large-scale problems, multi-agent cooperation has been in the limelight for the past few decades. Recently, many research projects have focused on context-aware cooperation to dynamically provide complex services. As cooperation in the multi-agent systems (MASs) becomes more common, guaranteeing the security of such cooperation takes on even greater importance. However, existing security models do not reflect the agents' unique features, including cooperation and context-awareness. In this paper, we propose a Community-based Role interaction-based Access Control model (CRiBAC) to allow secure cooperation in MASs. To do this, we refine and extend our preliminary RiBAC model, which was proposed earlier to support secure interactions among agents, by introducing a new concept of interaction permission, and then extend it to CRiBAC to support community-based cooperation among agents. We analyze potential problems related to interaction permissions and propose two approaches to address them. We also propose an administration model to facilitate administration of CRiBAC policies. Finally, we present the implementation of a prototype system based on a sample scenario to assess the proposed work and show its feasibility. © 2012 Elsevier Ltd. All rights reserved

Semiformal Verification of Embedded Software in Medical Devices Considering Stringent Hardware Constraints

In recent days, the complexity of software has increased significantly in embedded products in such a way that the verification of Embedded Software (ESW) now plays an important role to ensure the product's quality. Embedded systems engineers usually face the problems of verifying properties that have to meet the application's deadline, access the memory region, handle concurrency, and control the hardware registers. This work proposes a semiformal verification approach that combines dynamic and static verification to stress and cover exhaustively the state space of the system. We perform a case study on embedded software used in the medical devices domain. We conclude that the proposed approach improves the coverage and reduces substantially the verification time

A Formal Treatment of Sequential Ignorability

Taking a rigorous formal approach, we consider sequential decision problems involving observable variables, unobservable variables, and action variables. We can typically assume the property of extended stability, which allows identification (by means of G-computation) of the consequence of a specified treatment strategy if the unobserved variables are, in fact, observed - but not generally otherwise. However, under certain additional special conditions we can infer simple stability (or sequential ignorability), which supports G-computation based on the observed variables alone. One such additional condition is sequential randomization, where the unobserved variables essentially behave as random noise in their effects on the actions. Another is sequential irrelevance, where the unobserved variables do not influence future observed variables. In the latter case, to deduce sequential ignorability in full generality requires additional positivity conditions. We show here that these positivity conditions are not required when all variables are discrete.Comment: 25 pages, 5 figures, 1 tabl