285,959 research outputs found

    Trust dynamics for collaborative global computing

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    Recent advances in networking technology have increased the potential for dynamic enterprise collaborations between an open set of entities on a global scale. The security of these collaborations is a major concern, and requires novel approaches suited to this new environment to be developed. Trust management appears to be a promising approach. Due to the dynamic nature of these collaborations,dynamism in the formation, evolution and exploitation of trust is essential. In this paper we explore the properties of trust dynamics in this context. Trust is formed and evolves according to personal experience and recommendations. The properties of trust dynamics are expressed through a formal model of trust. Specific examples, based on an e-purse application scenario are used to demonstrate these properties

    Privacy, security, and trust issues in smart environments

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    Recent advances in networking, handheld computing and sensor technologies have driven forward research towards the realisation of Mark Weiser's dream of calm and ubiquitous computing (variously called pervasive computing, ambient computing, active spaces, the disappearing computer or context-aware computing). In turn, this has led to the emergence of smart environments as one significant facet of research in this domain. A smart environment, or space, is a region of the real world that is extensively equipped with sensors, actuators and computing components [1]. In effect the smart space becomes a part of a larger information system: with all actions within the space potentially affecting the underlying computer applications, which may themselves affect the space through the actuators. Such smart environments have tremendous potential within many application areas to improve the utility of a space. Consider the potential offered by a smart environment that prolongs the time an elderly or infirm person can live an independent life or the potential offered by a smart environment that supports vicarious learning

    Neurally Implementable Semantic Networks

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    We propose general principles for semantic networks allowing them to be implemented as dynamical neural networks. Major features of our scheme include: (a) the interpretation that each node in a network stands for a bound integration of the meanings of all nodes and external events the node links with; (b) the systematic use of nodes that stand for categories or types, with separate nodes for instances of these types; (c) an implementation of relationships that does not use intrinsically typed links between nodes.Comment: 32 pages, 12 figure

    The SECURE collaboration model

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    The SECURE project has shown how trust can be made computationally tractable while retaining a reasonable connection with human and social notions of trust. SECURE has produced a well-founded theory of trust that has been tested and refined through use in real software such as collaborative spam filtering and electronic purse. The software comprises the SECURE kernel with extensions for policy specification by application developers. It has yet to be applied to large-scale, multi-domain distributed systems taking different application contexts into account. The project has not considered privacy in evidence distribution, a crucial issue for many application domains, including public services such as healthcare and police. The SECURE collaboration model has similarities with the trust domain concept, embodying the interaction set of a principal, but SECURE is primarily concerned with pseudonymous entities rather than domain-structured systems
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