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Titlebook: Data Privacy Management and Autonomous Spontaneous Security; 4th International Wo Joaquin Garcia-Alfaro,Guillermo Navarro-Arribas,Yv Confer

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Distributed Privacy-Preserving Methods for Statistical Disclosure Controlndividual parts of the original data. We show that some perturbation methods do not allow a private distributed extension, whereas other methods do. Among the methods that allow a distributed privacy-preserving version, we can list noise addition, resampling and a new protection method, ., which is described and analyzed here for the first time.
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RDyMASS: Reliable and Dynamic Enforcement of Security Policies for Mobile Agent Systemsly enforce security policies in mobile agent systems in modular and reliable way. For this purpose, we combine formal methods and aspect oriented programming. We propose a three-step approach to enforce security policies in the form of aspects that will be generated through a reliable specification of security policies.
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Steve Kennewell,Howard Tanner,John ParkinsonFinally, we compare our results with obligation support in the state of the art. The key contribution of this work is to bridge the gap between specific mechanisms to enforce obligations and underspecified support for obligations in today’s access control and data handling policy languages.
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CIM Applications: A System Integrator’s ViewASRBAC, that allows the network nodes to manage the access control system by themselves. ASRBAC uses the distributed model ARBAC02 as a basis, and extends it with context-awareness, self-management and self-adaptation.
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Blind Equalization and Smart Antennasn the symmetric bilinear setting based on a . assumption. That is our assumption is tautological in the generic group model and is “efficiently falsifiable” in the sense that its problem instances are stated non-interactively and concisely (i.e., independently of the number of adversarial queries and other large quantities).
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