Trusted Group Coordination for Pervasive Computing Systems (TUCANS)

在过去的几年里，手持电脑和智能手机的需求一直在显著上升。移动计算设备的空前广泛采用，加上无线网络技术的实质性进步，创造了支持随时随地计算范式所需的基础设施。实施袭击并谋取不正当的经济利益。因此，在如此多的机会连接的设备和服务中，能够决定谁可以信任，将成为泛在计算成功的关键。在设计普适系统的信任管理模型时，我们认识到需要研究的两个主要要求：需要尽可能忠实地模仿人类信任推理的模型，以及需要正式地引出可用于评估和比较信任模型的质量的度量。结合群体动力学、微观经济理论、信念理论和社会网络理论，提出一种新的模型来解决普适系统中的分布式信任管理问题。我们将通过模拟和案例研究的方式，根据新定义的指标实施模型并评估其质量。

Over the past few years, demand for hand-held computers and smartphones has been rising significantly. The unprecedented widespread adoptionof mobile computing devices, coupled with substantial advances in wireless networking technologies, have created the infrastructure needed to support the anywhere-anytime computing paradigm. In a society that has already become used to, and dependent on, the rapid access to information sourcesand services, mostly as a consequence of experience with the fixed Internet, the provision of ubiquitous computing services will appear extremely attractive.Consumer demand is set to raise, and so is the number and range of services on offer. Quite inevitably, the expected commercial return will attract malicious subjects as well, that will exploit the very nature of pervasive computing (e.g., the relative ease with which services and information can be accessed, the anonymity of the entities we interact with, the speed with which new entities come into reach while others disappear, etc.) to perpetrate attacks and make unjust financial gains. Being able to decide who canbe trusted in this plethora of opportunistically connected devices and services will thus become key to the success of ubiquitous computing. In designing a trust management model for pervasive systems, we recognise two major requirements that demand investigation: the need for models that mimic human trust reasoning as faithfully as possible, and the need for the formal elicitation of metrics that can be used to assess and compare the qualityof trust models. We intend to propose new models to tackle the problem of distributed trust management in pervasive systems, by means of a combination of group dynamics, microeconomic theory, belief theory,and social network theory. We will implement the models and assess their quality with respect to the newly defined metrics, by means of simulation andcase studies.