Abstract of Doctoral Dissertation Trust Management for Mobile Computing Platforms

Providing a trustworthy mobile computing platform is crucial for mobile communications, services and applications. In this dissertation, we study methodologies and mechanisms that can be used to provide a trustworthy mobile computing platform. We also present an autonomic trust management solution for a component software middleware platform targeting at an embedded device, such as a mobile phone. In the first part of the dissertation, we firstly overview the literature background of trust modeling and trust management. We propose research methodologies on the basis of a conceptual architecture of a trusted mobile environment. Further, we present a methodology to bridge disjoint trusted domains in mobile computing and communications into a trustworthy system. The second part of the dissertation contains a mechanism to sustain trust among computing platforms. The mechanism builds up a trust relationship based on the Root Trust (RT) module at a trustee platform and ensures trust sustainability according to pre-defined conditions. These conditions are approved at the time of trust establishment and enforced through the use of the pre-attested RT module until the intended purpose is fulfilled. Through applying this mechanism, we introduce a Trusted Collaboration Infrastructure (TCI) for peer-to-peer devices in order to establish trust collaboration among distributed peers. In addition, this mechanism contributes to a mobile Virtual Private Network (VPN) for trusted mobile enterprise networking. The third part of the dissertation presents an autonomic trust management solution that can manage trust adaptively in a middleware component software platform. We develop a formal trust model to specify, evaluate, set up and ensure trust relationships that exist among system entities. We further present a trust management architecture that supports the implementation of the above model and adopts a number of algorithms for autonomic trust management at system runtime. In particular, special control modes can be applied into the platform to ensure trustworthiness. We develop a methodology for trust control mode prediction and selection on the basis of an adaptive trust control model in order to support autonomic trust management.