Advances in trusted network computing

With rapid development and increasing complexity of computer and communication networks, user requirements for trust in open, dynamic, heterogeneous, mobile, wireless, and distributed computing environments are becoming more demanding. As useful and innovative technologies, trusted network computing has been attracting researchers with significant attentions. The accepted papers in this special issue are devoted to the advanced developments and research addressing related theoretical and practical aspects on trusted network computing, and the contents are built on analytical modeling, experimental and simulation studies. The contributions of these papers are outlined in the succeeding text. With wide and close Internet accessibility, smart phones inevitably suffer security threats and information security management issues. Jang, Chang, and Tsai investigate the information security related trust issues through a user-based empirical study with the aim to study the relationships between smart phone users’ computer literacy, network literacy, knowledge on mobile phone viruses, and trust in information security management principles. Users in pervasive computing environments (PCEs) expect to access network resources and services at anytime and at anywhere, bringing significant convenience to the people’s daily life. However, PCEs can lead to serious security risks and problems with access control, because these resources can be accessed by anyone with a mobile device. Chen, Wang, and Deng propose a semantic distance-based trust model to handle the security challenges emerging in PCEs. The semantic distance between entities and between trust categories is adopted to calculate the trustworthiness more precisely. All entities in PCEs make independent decisions, which can maximize their own profit with the proposed trust model. The simulation experiments show that the presented model is able to increase the interaction success ratio between entities. The context factors are important for trust evaluation in e-commerce environments. Zhang, Wang, and Zhang target the contextual transaction trust problem and present a trust vector to outline the reputation profile of a seller. It aims to identify the context imbalance problem in forthcoming transactions that can cause a huge monetary loss for victim buyers. The authors then propose three new approaches to contextual transaction trust computation in e-commerce environments and show the merit of these schemes under different conditions via experiments based on both eBay datasets and large-scale synthetic datasets. Reputation models in mobile ad hoc networks are confrontedwith the problemof strategically reporting dishonest recommendations given by a selfish group whose purpose