7 resultados para mandatory access control framework

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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In this paper we follow a theory-based approach to study the assimilation of compliance software in highly regulated multinational enterprises. These relatively new software products support the automation of controls which are associated with mandatory compliance requirements. We use institutional and success factor theories to explain the assimilation of compliance software. A framework for analyzing the assimilation of Access Control Systems (ACS), a special type of compliance software, is developed and used to reflect the experiences obtained in four in-depth case studies. One result is that coercive, mimetic, and normative pressures significantly effect ACS assimilation. On the other hand, quality aspects have only a moderate impact at the beginning of the assimilation process, in later phases the impact may increase if performance and improvement objectives become more relevant. In addition, it turns out that position of the enterprises and compatibility heavily influence the assimilation process.

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Over the past several years, a number of design approaches in wireless mesh networks have been introduced to support the deployment of wireless mesh networks (WMNs). We introduce a novel wireless mesh architecture that supports authentication and authorisation functionalities, giving the possibility of a seamless WMN integration into the home's organization authentication and authorisation infrastructure. First, we introduce a novel authentication and authorisation mechanism for wireless mesh nodes. The mechanism is designed upon an existing federated access control approach, i.e. the AAI infrastructure that is using just the credentials at the user's home organization in a federation. Second, we demonstrate how authentication and authorisation for end users is implemented by using an existing web-based captive portal approach. Finally, we observe the difference between the two and explain in detail the process flow of authorized access to network resources in wireless mesh networks. The goal of our wireless mesh architecture is to enable easy broadband network access to researchers at remote locations, giving them additional advantage of a secure access to their measurements, irrespective of their location. It also provides an important basis for the real-life deployment of wireless mesh networks for the support of environmental research.

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The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.

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Introduction: Video‐Supported Learning is particularly effective when it comes to skills and behaviors. Video registration of patient‐physician interviews, class room instruction or practical skills allow it to learners themselves, their peers, and their tutors to assess the quality of the learner's performance, to give specific feedback, and to make suggestions for improvement. Methods: In Switzerland, four pedagogical universities and two medical faculties joined to initiate the development of a national infrastructure for Video Supported Learning. The goal was to have a system that is simple to use, has most steps automated, provides the videos over the Internet, and has a sophisticated access control. Together with SWITCH, the national IT‐Support‐Organisation for Swiss Universities, the program iVT (Individual Video Training) was developed by integrating two preexisting technologies. The first technology is SWITCHcast, a podcast system. With SWITCHcast, videos are automatically uploaded to a server as soon as the registration is over. There the videos are processed and converted to different formats. The second technology is the national Single Logon System AAI (Authentification and Authorization Infrastructure) that enables iVT to link each video with the corresponding learner. The learner starts the registration with his Single Logon. Thus, the video can unambiguously be assigned. Via his institution's Learning Management System (LMS), the learner can access his video and give access to his video to peers and tutors. Results: iVT is now used at all involved institutions. The system works flawlessly. In Bern, we use iVT for the communications skills training in the forth and sixth year. Since students meet with patient actors alone, iVT is also used to certify attendance. Students are encouraged to watch the videos of the interview and the feedback of the patient actor. The offer to discuss a video with a tutor was not used by the students. Discussion: We plan to expand the use of iVT by making peer assessment compulsory. To support this, annotation capabilities are currently added to iVT. We also want to use iVT in training of practical skills, again for self as well as for peer assessment.  At present, we use iVT for quality control of patient actor's performance.

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Location prediction has attracted a significant amount of research effort. Being able to predict users’ movement benefits a wide range of communication systems, including location-based service/applications, mobile access control, mobile QoS provision, and resource management for mobile computation and storage management. In this demo, we present MOBaaS, which is a cloudified Mobility and Bandwidth prediction services that can be instantiated, deployed, and disposed on-demand. Mobility prediction of MOBaaS provides location predictions of a single/group user equipments (UEs) in a future moment. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operations. We demonstrate an example of real-time mobility prediction service deployment running on OpenStack platform, and the potential benefits it bring to other invoking services.