Implementing Operating System Support for Extended Trusted Path in TPM-Capable Environments

Trusted path is one of the crucial features that operating systems must provide for fundamental security support. In order to explore the possibility of implementing a trusted path mechanism with the support of trusted platform module （TPM） technologies, and to support TPM capabilities in operating systems, the paper extended the scope of the conventional trusted path to cover the situation in which a user communicates with software residing on a remote host. The paper combined the concept of operating system support for trusted path with that for TPM platforms, and proposed the architecture of an extended trusted path mechanism in operating system with considerations on TPM-capable platforms support. As part of the author＇s research in secure operating systems, the work of the paper was carried out with Linux as an experimental prototype system. The research result shows that TPM capabilities can strengthen extended trusted path mechanisms of operating systems.

Density-based rough set model for hesitant node clustering in overlapping community detection

Overlapping community detection in a network is a challenging issue which attracts lots of attention in recent years.A notion of hesitant node（HN） is proposed. An HN contacts with multiple communities while the communications are not strong or even accidental, thus the HN holds an implicit community structure.However, HNs are not rare in the real world network. It is important to identify them because they can be efficient hubs which form the overlapping portions of communities or simple attached nodes to some communities. Current approaches have difficulties in identifying and clustering HNs. A density-based rough set model（DBRSM） is proposed by combining the virtue of densitybased algorithms and rough set models. It incorporates the macro perspective of the community structure of the whole network and the micro perspective of the local information held by HNs, which would facilitate the further ＂growth＂ of HNs in community. We offer a theoretical support for this model from the point of strength of the trust path. The experiments on the real-world and synthetic datasets show the practical significance of analyzing and clustering the HNs based on DBRSM. Besides, the clustering based on DBRSM promotes the modularity optimization.

Research Progress of Trust Evaluation Model

Software systems in distributed environment are changing from a close and relatively static form, whose users are familiar with each other, to an open and highly dynamic mode, which can be visited by public. In such circumstance, trust evaluation model becomes focus of intense research at current time. Trust evaluation model establishes a management framework of trust relationship between entities, involving expression and measurement of trust, comprehensive calculation of direct trust value and recommended trust value, and recognition of malicious entities and recommendations. Based on the analysis of several typical trust evaluation models, the classification of trust evaluation ideas and modes is discussed, the questions existing in current research and the directions of future research are pointed out.